20 Catboost Jobs

As an AI/ML Manager at our Pune location, you will be responsible for leading the development of machine learning proof of concepts (PoCs) and demos using structured/tabular data for various use cases like forecasting, risk scoring, churn prediction, and optimization. Your role will involve collaborating with sales engineering teams to understand client requirements and presenting ML solutions during pre-sales calls and technical workshops. You will be expected to build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML, managing training, tuning, evaluation, and model packaging. Applying supervised, unsupervised, and semi-supervised techniques like XGBoost, CatBoost, k-Means, PCA, and time-series models will be a key part of your responsibilities. Working closely with data engineering teams, you will define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Packaging and documenting ML assets for scalability and transition into delivery teams post-demo will be essential. Staying updated with the latest best practices in ML explainability, model performance monitoring, and MLOps practices is also expected. Participation in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes are additional aspects of this role. To qualify for this position, you should have at least 8+ years of experience in developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries like XGBoost, CatBoost, LightGBM is required. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks is preferred. A solid understanding of feature engineering, model tuning, cross-validation, and error analysis is necessary. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques will be beneficial. You should be comfortable presenting models and insights to both technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection, will be an advantage. If you are interested in this opportunity, please apply or share your resume at kanika.garg@austere.co.in.,

AI/ML Manager: Location – Pune Experience: 8+ years Notice period – Immediate to 30 days. Key Responsibilities: Lead the development of machine learning PoCs and demos using structured/tabular data for use cases such as forecasting, risk scoring, churn prediction, and optimization. Collaborate with sales engineering teams to understand client needs and present ML solutions during pre-sales calls and technical workshops. Build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML and manage training, tuning, evaluation, and model packaging. Apply supervised, unsupervised, and semi-supervised techniques such as XGBoost, CatBoost, k-Means, PCA, time-series models, and more. Work with data engineering teams to define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Package and document ML assets so they can be scaled or transitioned into delivery teams post-demo. Stay current with best practices in ML explainability, model performance monitoring, and MLOps practices. Participate in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes. Qualifications: 8+ years of experience developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries such as XGBoost, CatBoost, LightGBM, etc. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks. Solid understanding of feature engineering, model tuning, cross-validation, and error analysis. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques. Comfortable presenting models and insights to technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection. Interested candidates shall apply or share resumes at kanika.garg@austere.co.in.

Job Description Design and develop machine learning models tailored to mechanical engineering challenges, including predictive modelling, simulation optimisation, and failure analysis. Utilise deep learning and other advanced ML techniques to improve the accuracy and efficiency of CAE simulations. Preprocess and analyse large datasets from CAE simulations, experimental tests, and manufacturing processes for modelling. Train, validate, and fine-tune machine learning models using real-world engineering data. Optimise models for performance, scalability, and robustness in production environments. Collaborate with CAE engineers to integrate ML models into existing simulation workflows (e.g., FEA, CFD, structural analysis). Automate repetitive simulation tasks and enable predictive analytics for design optimisation. Work closely with mechanical engineers, data scientists, and software developers to identify business challenges and develop data-driven solutions. Deploy machine learning models into production environments and monitor their performance. Maintain and update models to ensure reliability and continuous improvement. Stay abreast of the latest advancements in machine learning, AI, and CAE technologies. Apply innovative approaches to solve complex engineering problems. Requirements Bachelors or Master’s degree in Mechanical Engineering, Computer Science, or a related field Proven 2-3 years of experience in developing and deploying machine learning models, preferably in mechanical engineering or CAE domain Hands-on experience with CAE tools such as ANSYS, Abaqus, or similar FEA/CFD software Strong programming skills in Python, R, or Java Proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn) Experience with data preprocessing, feature engineering, and statistical analysis Solid understanding of mathematics, statistics, and problem-solving skills Excellent analytical thinking and ability to tackle complex engineering challenges Strong communication and teamwork skills to collaborate across disciplines Preferred: Experience with physics-informed machine learning and digital twin technologies Preferred: Familiarity with automation of CAE workflows and predictive modelling for product design Benefits Challenging job and a chance to team up with a young and dynamic professional group Chance to build yourself as WE grow. Remuneration that stays competitive and attractive to retain the best. Opportunity to join an organization experiencing year on year growth.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities: Work closely with a lead-data scientist and help improve business processes leveraging data science tools & techniques in natural language and machine learning domain Understand business requirements and convert into analytical solution Analyze large amounts of information to discover trends and patterns Develop data science algorithms & generate actionable insights as per business needs and work closely with cross capability teams throughout solution development lifecycle from design to implementation & monitoring Understanding of Azure Cloud technologies such as Azure Data Factory, Azure SQL, Azure Blob Storage Azure data Bricks Manage day to day development tasks and stakeholder communication Document work appropriately for production support and transition readiness Acquire & enhance understanding of US Healthcare domain Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Masters in Mathematics, Computer Science, Statistics or Machine Learning - any or equivalent 12+ months hands on experience of solving real world business problems leveraging data science tools Working knowledge of NLP skills (like Text Classification/Entity Recognition/Transfer Learning Concepts etc.) Sound knowledge of unstructured text data handling & manipulation; Programming: Python/SQL knowledge Good Theoretical knowledge of some or most Machine learning techniques like Random Forest, Gradient Boosting Machine, XGBoost, CATBoost etc. Programming: knows R/Python with PyTorch/TensorFlow, Knows how to leverage pre trained models (Via Transfer Learning) Proven excellent written and oral communication skills Proven excellent problem-solving & story-telling abilities with analytical mindset Proven excellent interpersonal and team skills Preferred Qualifications: Understanding & experience of SparkNLP framework Understanding of Responsible Use of AI, model fairness, bias assessment and its risk mitigations Exposure to RAG, LangChain, VectorDBs At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities Work closely with a lead-data scientist and help improve business processes leveraging data science tools & techniques in natural language and machine learning domain Understand business requirements and convert into analytical solution Analyze large amounts of information to discover trends and patterns Develop data science algorithms & generate actionable insights as per business needs and work closely with cross capability teams throughout solution development lifecycle from design to implementation & monitoring Understanding of Azure Cloud technologies such as Azure Data Factory, Azure SQL, Azure Blob Storage Azure data Bricks Manage day to day development tasks and stakeholder communication Document work appropriately for production support and transition readiness Acquire & enhance understanding of US Healthcare domain Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Masters in Mathematics, Computer Science, Statistics or Machine Learning - any or equivalent 12+ months hands on experience of solving real world business problems leveraging data science tools Working knowledge of NLP skills (like Text Classification/Entity Recognition/Transfer Learning Concepts etc.) Sound knowledge of unstructured text data handling & manipulation; Programming: Python/SQL knowledge Good Theoretical knowledge of some or most Machine learning techniques like Random Forest, Gradient Boosting Machine, XGBoost, CATBoost etc. Programming: knows R/Python with PyTorch/TensorFlow, Knows how to leverage pre trained models (Via Transfer Learning) Proven excellent written and oral communication skills Proven excellent problem-solving & story-telling abilities with analytical mindset Proven excellent interpersonal and team skills Preferred Qualifications Understanding & experience of SparkNLP framework Understanding of Responsible Use of AI, model fairness, bias assessment and its risk mitigations Exposure to RAG, LangChain, VectorDBs At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

AI / Machine Learning / Data Science part time Work from Home (Any where in world) Warm Greetings from Excel Online Classes, We are a team of industry professionals running an institute that provides comprehensive online IT training, technical support, and development services. We are currently seeking AI / Machine Learning / Data Science Experts who are passionate about technology and can collaborate with us in their free time. If you're enthusiastic, committed, and ready to share your expertise, we would love to work with you! Were hiring for the following services: Online Training Online Development Online Technical Support Conducting Online Interviews Corporate Training Proof of Concept (POC) Projects Research & Development (R&D) We are looking for immediate joiners who can contribute in any of the above areas. If you're interested, please fill out the form using the link below: https://docs.google.com/forms/d/e/1FAIpQLSdvut0tujgMbBIQSc6M7qldtcjv8oL1ob5lBc2AlJNRAgD3Cw/viewform We also welcome referrals! If you know someone—friends, colleagues, or connections—who might be interested in: Teaching, developing, or providing tech support online Sharing domain knowledge (e.g., Banking, Insurance, etc.) Teaching foreign languages (e.g., Spanish, German, etc.) Learning or brushing up on technologies to clear interviews quickly Upskilling in new tools or frameworks for career growth Please feel free to forward this opportunity to them. For any queries, feel free to contact us at: excel.onlineclasses@gmail.com Thank you & Best Regards, Team Excel Online Classes excel.onlineclasses@gmail.com

AI/ML Engineer/Manager: Location – Pune Experience: 6+ years Notice period – Immediate to 30 days. Key Responsibilities: Lead the development of machine learning PoCs and demos using structured/tabular data for use cases such as forecasting, risk scoring, churn prediction, and optimization. Collaborate with sales engineering teams to understand client needs and present ML solutions during pre-sales calls and technical workshops. Build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML and manage training, tuning, evaluation, and model packaging. Apply supervised, unsupervised, and semi-supervised techniques such as XGBoost, CatBoost, k-Means, PCA, time-series models, and more. Work with data engineering teams to define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Package and document ML assets so they can be scaled or transitioned into delivery teams post-demo. Stay current with best practices in ML explainability , model performance monitoring , and MLOps practices. Participate in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes. Qualifications: 8+ years of experience developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python , pandas , scikit-learn , and ML libraries such as XGBoost, CatBoost , LightGBM, etc. Familiarity with cloud-based ML environments such as AWS SageMaker , Azure ML , or Databricks . Solid understanding of feature engineering, model tuning, cross-validation, and error analysis . Experience with unsupervised learning , clustering, anomaly detection, and dimensionality reduction techniques. Comfortable presenting models and insights to technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts , including model versioning, deployment automation, and drift detection. Interested candidates shall apply or share resumes at kanika.garg@austere.co.in.

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What You'll Do You will play an important role in applying and implementing effective machine learning solutions, with a significant focus on Generative AI. You will work with product and engineering teams to contribute to data-driven product strategies, explore and implement GenAI applications, and deliver impactful insights. This positionis an individual contributor role reporting to the Senior Manager, Data Science. Responsibility Experiment with, apply, and implement DL/ML models, with a strong emphasis on Large Language Models (LLMs), Agentic Frameworks, and other Generative AI techniques to predict user behavior, enhance product features, and improve automation Utilize and adapt various GenAI techniques (e.g., prompt engineering, RAG, fine-tuning existing models) to derive actionable insights, generate content, or create novel user experiences Collaborate with product, engineering, and other teams (e.g., Sales, Marketing, Customer Success) to build Agentic system to run campaigns at-scale Conduct in-depth analysis of customer data, market trends, and user insights to inform the development and improvement of GenAI-powered solutions Partner with product teams to design, administer, and analyze the results of A/B and multivariate tests, particularly for GenAI-driven features Leverage data to develop actionable analytical insights & present findings, including the performance and potential of GenAI models, to stakeholders and team members Communicate models, frameworks (especially those related to GenAI), analysis, and insights effectively with stakeholders and business partners Stay updated on the latest advancements in Generative AI and propose their application to relevant business problems Complete assignments with a sense of urgency and purpose, identify and help resolve roadblocks, and collaborate with cross-functional team members on GenAI initiatives Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What You Bring Basic Bachelor's or Master's degree in Computer Science, Physics, Mathematics, Statistics, or a related field 3+ years of hands-on experience in building data science applications and machine learning pipelines, with demonstrable experience in Generative AI projects Experience with Python for research and software development purposes, including common GenAI libraries and frameworks Experience with or exposure to prompt engineering, and utilizing pre-trained LLMs (e.g., via APIs or open-source models) Experience with large datasets, distributed computing, and cloud computing platforms (e.g., AWS, Azure, GCP) Proficiency with relational databases (e.g., SQL) Experience in training, evaluating, and deploying machine learning models in production environments, with an interest in MLOps for GenAI Proven track record in contributing to ML/GenAI projects from ideation through to deployment and iteration Experience using machine learning and deep learning algorithms like CatBoost, XGBoost, LGBM, Feed Forward Networks for classification, regression, and clustering problems, and an understanding of how these can complement GenAI solutions Experience as a Data Scientist, ideally in the SaaS domain with some focus on AI-driven product features Preferred PhD in Statistics, Computer Science, or Engineering with specialization in machine learning, AI, or Statistics, with research or projects in Generative AI 5+ years of prior industry experience, with at least 1-2 years focused on GenAI applications Previous experience applying data science and GenAI techniques to customer success, product development, or user experience optimization Hands-on experience with fine-tuning LLMs or working with RAG methodologies Experience with or knowledge of experimentation platforms (like DataRobot) and other AI related ones (like CrewAI) Experience with or knowledge of the software development lifecycle/agile methodology, particularly in AI product development Experience with or knowledge of Github, JIRA/Confluence Contributions to open-source GenAI projects or a portfolio of GenAI related work Programming Languages like Python, SQL; familiarity with R Strong knowledge of common machine learning, deep learning, and statistics frameworks and concepts, with a specific understanding of Large Language Models (LLMs), transformer architectures, and their applications Ability to break down complex technical concepts (including GenAI) into simple terms to present to diverse, technical, and non-technical audiences Life At Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Our global benefits Paid time off Take time to unwind with earned days off, plus paid company holidays based on your region. Paid parental leave Take up to six months off with your child after birth, adoption or foster care placement. Full health benefits Options for 100% employer-paid health plans from day one of employment. Retirement plans Select retirement and pension programs with potential for employer contributions. Learning & development Grow your career with coaching, online courses and education reimbursements. Compassionate care leave Paid time off following the loss of a loved one and other life-changing events.

Machine Learning Engineer (L1) Experience Required: 2-4 years As a Machine Learning Engineer at Spring, you’ll help bring data-driven intelligence into our products and operations. You’ll support the development and deployment of models and pipelines that power smarter decisions, more personalized experiences, and scalable automation. This is an opportunity to build hands-on experience in real-world ML and AI systems while collaborating with experienced engineers and data scientists. You’ll work on data processing, model training, and integration tasks — gaining exposure to the entire ML lifecycle, from experimentation to production deployment. You’ll learn how to balance model performance with system requirements, and how to structure your code for reliability, observability, and maintainability. You’ll use modern ML/AI tools such as scikit-learn, HuggingFace, and LLM APIs — and be encouraged to explore AI techniques that improve our workflows or unlock new product value. You’ll also be expected to help build and support automated data pipelines, inference services, and validation tools as part of your contributions. You’ll work closely with engineering, product, and business stakeholders to understand how models drive value. Over time, you’ll build the skills and judgment needed to identify impactful use cases, communicate technical trade-offs, and contribute to the broader evolution of ML at Spring. What You’ll Do Support model development and deployment across structured and unstructured data and AI use cases. Build and maintain automated pipelines for data processing, training, and inference. Use ML and AI tools (e.g., scikit-learn, LLM APIs) in day-to-day development. Collaborate with engineers, data scientists, and product teams to scope and deliver features. Participate in code reviews, testing, and monitoring practices. Integrate ML systems into customer-facing applications and internal tools. Identify differences in data distribution that could affect model performance in real-world applications. Stay up to date with developments in the machine learning industry. Tech Expectations Core Skills Curiosity, attention to detail, strong debugging skills, and eagerness to learn through feedback Solid foundation in statistics and data interpretation Strong understanding of data structures, algorithms, and software development best practices Exposure to data pipelines, model training and evaluation, or training workflows Languages Must Have: Python, SQL ML Algorithms Must Have: Traditional modeling techniques (e.g., tree models, Naive Bayes, logistic regression) Ensemble methods (e.g., XGBoost, Random Forest, CatBoost, LightGBM) ML Libraries / Frameworks Must Have: scikit-learn, Hugging Face, Statsmodels, Optuna Good to Have: SHAP, Pytest Data Processing / Manipulation Must Have: pandas, NumPy Data Visualization Must Have: Plotly, Matplotlib Version Control Must Have: Git Others – Good to Have AWS (e.g., EC2, SageMaker, Lambda) Docker Airflow MLflow Github Actions

Title: Senior Machine Learning Engineer Location: Gurgaon, IN Type: (Hybrid, In-Office) Job Description Who We Are: Fareportal is a travel technology company powering a next-generation travel concierge service. Utilizing its innovative technology and company owned and operated global contact centres, Fareportal has built strong industry partnerships providing customers access to over 500 airlines, a million lodgings, and hundreds of car rental companies around the globe. With a portfolio of consumer travel brands including CheapOair and OneTravel, Fareportal enables consumers to book-online, on mobile apps for iOS and Android, by phone, or live chat. Fareportal provides its airline partners with access to a broad customer base that books high-yielding international travel and add-on ancillaries. HIGHLIGHTS : Fareportal is the number 1 privately held online travel company in flight volume. Fareportal partners with over 500 airlines, 1 million lodgings, and hundreds of car rental companies worldwide. 2019 annual sales exceeded $5 billion. Fareportal sees over 150 million unique visitors annually to our desktop and mobile sites. Fareportal, with its global workforce of over 2,600 employees, is strategically positioned with 9 offices in 6 countries and headquartered in New York City. What We Do Our Machine Learning team is at the forefront of developing state-of-the-art models and solutions that drive key business decisions, improve customer experiences, and streamline operations. We work on diverse projects, from personalized recommendations and predictive modelling to call analytics and business forecasting, using cutting-edge technology and data-driven insights. Our department is unique in its end-to-end approach to problem-solving, focusing on innovation, collaboration, and impactful results. As a Senior Machine Learning Engineer, you will play a crucial role in the complete lifecycle of our Machine Learning projects. You will: - Engage with stakeholders to gather and refine requirements. - Perform exploratory data analysis (EDA) and manipulate data using SQL and NoSQL databases. - Engineer and select features, ensuring optimal model performance. - Train, test, and fine-tune models using advanced algorithms and methodologies. - Deploy models into production environments using frameworks like Docker, Kubernetes, and Rest APIs. - Monitor and evaluate model performance, including A/B testing and continuous improvement. - Collaborate with cross-functional teams, ensuring seamless integration and communication throughout the project lifecycle. In this Role You Will Get To - Work within a dynamic and talented team of engineers and data scientists to build scalable Machine Learning solutions that impact thousands of users daily. - Develop, deploy, and maintain Machine Learning models that address complex business challenges and enhance customer engagement. - Participate in brainstorming sessions, technical design discussions, and collaborate with product managers, data engineers, and other stakeholders to ensure alignment and success. - Explore and implement new technologies, including cloud-based (AWS, Azure) and on-prem systems, to optimize and enhance ML model performance. - Conduct rigorous testing and monitoring to ensure the reliability and accuracy of models. Who You Are Must-Haves: - Strong communication skills, capable of translating technical concepts into actionable business insights. - Proven experience (2-4 years) as a Data Scientist, Machine Learning Engineer, or in a similar role. - Proficient in SQL querying for data extraction and manipulation. - Experience with high volume structured data, including data manipulation, exploratory data analysis (EDA), and data modelling. - Strong proficiency in Python programming and familiarity with Rest API frameworks for seamless model integration. - Demonstrated ability to build and deploy at least 3-5 ML models in production environments. - Hands-on experience with Regression, Classification, Recommendation algorithms, and Neural Networks. - Expertise in relevant ML libraries such as CatBoost, XGBoost, LightGBM, Scikit-learn, TensorFlow, and PyTorch. - Knowledge of containerization technologies (e.g., Docker, Kubernetes) and virtual machines (VMs). - Familiarity with cloud (AWS/Azure) and on-prem data systems. - Bachelors in computer science, or a related field; a Master's degree is a plus. Good-to-Haves: - Experience working with distributed data processing frameworks like PySpark. - Experience working with Natural Language Processing (NLP) and Large Language Models (LLMs). - Familiarity with MLOps platforms such as MLFlow and Kubeflow. - Prior experience with A/B testing methodologies. - Advanced skills in data visualization tools like Tableau or Power BI. Disclaimer This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Fareportal reserves the right to change the job duties, responsibilities, expectations, or requirements posted here at any time at the Company's sole discretion, with or without notice.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Data Scientist II-3 Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview Finicity, a Mastercard company, is leading the Open Banking Initiative to increase the Financial Health of consumers and businesses. The Data Science and Analytics team is looking for a Data Scientist II. The Data Science team works on Intelligent Decisioning; Financial Certainty; Attribute, Feature, and Entity Resolution; Verification Solutions and much more. Join our team to make an impact across all sectors of the economy by consistently innovating and problem-solving. The ideal candidate is passionate about leveraging data to provide high quality customer solutions. Also, the candidate is a strong technical leader who is extremely motivated, intellectually curious, analytical, and possesses an entrepreneurial mindset. Role Manipulates large data sets and applies various technical and statistical analytical techniques (e.g., OLS, multinomial logistic regression, LDA, clustering, segmentation) to draw insights from large datasets. Apply various Machine learning (i.e. SVM, Radom Forest, XGBoost, LightGBM, CATBoost etc), Deep learning techniques (i.e. LSTM, RNN, Transformer etc.) to solve analytical problem statement. Design and implement machine learning models for a number of financial applications including but not limited to: Transaction Classification, Temporal Analysis, Risk modeling from structured and unstructured data. Measure, validate, implement, monitor and improve performance of both internal and external facing machine learning models. Propose creative solutions to existing challenges that are new to the company, the financial industry and to data science. Present technical problems and findings to business leaders internally and to clients succinctly and clearly. Leverage best practices in machine learning and data engineering to develop scalable solutions. Identify areas where resources fall short of needs and provide thoughtful and sustainable solutions to benefit the team Be a strong, confident, and excellent writer and speaker, able to communicate your analysis, vision and roadmap effectively to a wide variety of stakeholders All About You: 3-5 years in data science/ machine learning model development and deployments Exposure to financial transactional structured and unstructured data, transaction classification, risk evaluation and credit risk modeling is a plus. A strong understanding of NLP, Statistical Modeling, Visualization and advanced Data Science techniques/methods. Gain insights from text, including non-language tokens and use the thought process of annotations in text analysis. Solve problems that are new to the company, the financial industry and to data science SQL / Database experience is preferred Experience with Kubernetes, Containers, Docker, REST APIs, Event Streams or other delivery mechanisms. Familiarity with relevant technologies (e.g. Tensorflow, Python, Sklearn, Pandas, etc.). Strong desire to collaborate and ability to come up with creative solutions. Additional Finance and FinTech experience preferred. Bachelor’s or Master’s Degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics. Corporate Security Responsibility Every Person Working For, Or On Behalf Of, Mastercard Is Responsible For Information Security. All Activities Involving Access To Mastercard Assets, Information, And Networks Comes With An Inherent Risk To The Organization And Therefore, It Is Expected That The Successful Candidate For This Position Must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. #AI Corporate Security Responsibility All Activities Involving Access To Mastercard Assets, Information, And Networks Comes With An Inherent Risk To The Organization And, Therefore, It Is Expected That Every Person Working For, Or On Behalf Of, Mastercard Is Responsible For Information Security And Must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-247687

Data Scientist Location: Pune (Baner) - Onsite, with possible options of Hybrid Contract: Full-time Salary: Competitive depending on experience. About Protect Group: Protect Group, established in 2016, is an innovative global technology leader enhancing customer experiences and revenue opportunities for businesses through AI-driven solutions. With over 400 partners across 75+ countries, we provide an intuitive widget that seamlessly integrates with online sales platforms, dramatically improving customer satisfaction and boosting ancillary revenue. Our culture is defined by ambition, innovation, and excellence—our Protect People embody these values, making a significant impact across sectors including travel, hospitality, transportation, events, and financial services. Role Overview: We are seeking a talented Data Scientist to play a central role in our global data team. You'll lead analytical initiatives, driving experimentation and optimisation in pricing strategies, significantly influencing our product insights and commercial decision-making. You’ll leverage your expertise in advanced analytics, machine learning, and statistical modelling to derive actionable insights from complex datasets. Key Responsibilities: Analyse large online datasets to uncover valuable insights into consumer behaviour, price elasticity, and revenue optimisation. Collaborate with Product, Technology, Marketing and Sales teams. Contribute insights towards the development and refinement of predictive models used to forecast demand and optimise pricing and content. Create clear and intuitive dashboards and visualisations to communicate insights effectively, facilitating strategic business decisions. Act as a data analytics specialist, encouraging a culture of informed, data-driven decision-making throughout the organisation. Required Skills & Experience: Extensive experience conducting data analysis within relevant sectors. Proficiency in SQL, Python, and data science libraries such as sklearn, XGBoost, and CatBoost. Experience with Azure, MLOps, and API frameworks. Strong understanding of statistical methods, probability theory, pricing optimisation, and elasticity modelling. Expertise with data visualisation tools (e.g., Tableau). Exceptional analytical and creative problem-solving skills, with meticulous attention to detail. Excellent communication skills—capable of articulating complex analytical findings clearly and effectively. Adaptable, innovative, and self-driven, comfortable in fast-paced, agile environments. Why Protect Group? Join a rapidly scaling tech company revolutionising global industries. Lead impactful analyses that directly shape strategic decisions and commercial outcomes. Work within a talented team dedicated to innovation and continuous improvement. Ready to Join Us? If you're passionate about analytics and keen to drive meaningful insights, we want to hear from you! Submit your CV today and share how you'll contribute to Protect Group’s continued success. ***Please note we will be considering those who are currently residing in Pune first. Show more Show less

About The Role We are seeking a highly skilled and hands-on Senior Data Scientist with 7+ years of experience to lead the design and implementation of robust machine learning pipelines and drive data-driven decision making across the organization. This role requires a strategic thinker who can bridge the gap between complex data science concepts and practical business solutions, while ensuring model integrity, explainability, and compliance in production environments. As a Senior Data Scientist, you will have end-to-end ownership of the model life cycle, from data ingestion and feature engineering to model deployment, monitoring, and governance. Youll work closely with AI engineers, product teams, and stakeholders to deliver high-impact solutions that drive business value. Key Responsibilities Machine Learning & Predictive Modeling : Design and build sophisticated predictive models using Scikit-learn, XG Boost, LightGBM, and CatBoost for various use cases. Develop advanced forecasting models using Prophet, ARIMA, and neural forecasting techniques for time series analysis. Implement anomaly detection systems and risk scoring models for fraud detection and security applications Create recommendation systems and personalization algorithms using collaborative filtering and deep learning approaches AI Integration & Pipeline Development Collaborate with AI engineers to integrate traditional ML components into LangChain and LLM-driven intelligent systems Design hybrid architectures that combine classical ML with generative AI for enhanced business solutions Develop evaluation frameworks for comparing traditional ML and LLM based approaches Implement retrieval systems that enhance LLM performance with domain specific knowledge Model Lifecycle Management Automate comprehensive model lifecycle processes including training, validation, deployment, and rollback procedures Implement continuous training pipelines using MLFlow, Kubeflow, and Weights & Biases Design and maintain model monitoring systems for drift detection, performance degradation, and data quality issues Establish model governance frameworks ensuring reproducibility and auditability Data Validation & Quality Assurance Lead the development of pre-model and post-model validation frameworks using DeepChecks, Great Expectations, and custom validation rules Implement fairness and bias detection systems using Fairlearn and custom algorithmic auditing tools Design comprehensive data quality monitoring and alerting systems Conduct statistical testing and hypothesis validation for model performance claims Compliance & Security Ensure PII protection and DPDP compliance through secure data preprocessing and anonymization techniques Implement synthetic data generation pipelines using Gretel.ai and other privacy-preserving technologies Design policy-driven access controls and data governance frameworks using Apache Griffin and DataHub Conduct privacy impact assessments and implement differential privacy techniques where applicable Model Explainability & Auditing Develop comprehensive model explainability frameworks using SHAP, LIME, and custom interpretation tools Conduct reasoning-based walkthroughs and accuracy audits for deployed models Perform bias analysis and fairness assessments across different demographic groups Design and implement A/B testing frameworks for model performance evaluation Data Engineering & Pipeline Architecture Design and implement scalable ETL/ELT pipelines using Apache Spark, Flink, and modern data processing frameworks Leverage Redis for intelligent caching strategies and real-time feature serving Implement streaming data processing using Apache Kafka, RabbitMQ, and event-driven architectures Optimize data pipeline performance and ensure data consistency across distributed systems (ref:hirist.tech) Show more Show less

Job Purpose - Understand Business Processes & Data, Model the requirements to create Analytics Solutions Build Predictive Models & Recommendation Engines using state-of-the-art Machine Learning Techniques to aid Business Processes increase efficiency and effectiveness in their outcomes. Churn and Analyze the data to discover actionable insights & patterns for Business use. Assist the Function Head in Data Preparation & Modelling Tasks as required JobOutline - Collaborate with Business and IT teams for understanding and collecting data. Collect, collate, clean, process and transform large volume(s) of primarily Tabular data (Blend of Numerical, Categorical & some Text). Apply Data Preparation Techniques like Data Filtering, Joining, Cleaning, Missing Value imputation, Feature Extraction, Feature Engineering, Feature Selection, Dimensionality Reduction, Feature Scaling, Variable Transformation etc Apply as required: basic Algorithms like Linear Regression, Logistic Regression, ANOVA, KNN, Clustering (K-Means, Density, Hierarchical etc), SVM, Naïve Bayes, Decision Trees, Principal Components, Association Rule Mining etc. Apply as required: Ensemble Modeling algorithms like Bagging (Random Forest), Boosting (GBM, LGBM, XGBoost, CatBoost), Time-Series Modelling and other state-of-the-art Algorithms. Apply as required: Modelling concepts like Hyperparameter Optimization, Feature Selection, Stacking, Blending, K-Fold Cross-Validation, Bias & Variance, Overfitting etc Build Predictive Models using state-of-the-art Machine Learning techniques for Regression, Classification, Clustering, Recommendation Engines etc Perform Advance Analytics of the Business Data to find hidden patterns & insights, explanatory causes, and make strategic business recommendations based on the same Knowledge /Education BE /B. Tech – Any Stream Skills Should have strong expertise in Python libraries like Pandas & Scikit Learn along with ability to code according to requirements stated in the Job Outline above Experience of Python Editors like PyCharm and/or Jupyter Notebooks (or other editors) is a must. Ability to organize the code into Modules, Functions and/or Objects is a must Knowledge of using ChatGPT for ML will be preferred. Familiarity with basic SQL for Querying & Excel for Data Analysis is a must. Should understand basics of Statistics like Distributions, Hypothesis Testing, Sampling Techniques etc Work Experience Have an experience of at least 4 years of solving Business Problems through Data Analytics, Data Science and Modelling. Should have experience as a full-time Data Scientist for at least 2 years. Experience of at least 3 Projects in ML Model building, which were used in Production by Business or other clients Skills/Experience Preferred but not compulsory - Familiarity with using ChatGPT, LLMs, Out-of-the Box Models etc for Data Preparation & Model building Kaggle experience. Familiarity with R. Job Interface/Relationships: Internal Work with different Business Teams to build Predictive Models for them External None Key Responsibilities and % Time Spent Data Preparation for Modelling - Data Extraction, Cleaning, Joining & Transformation - 35% Build ML/AI Models for various Business Requirements - 35% Perform Custom Analytics for providing actionable insights to the Business - 20% Assist the Function Head in Data Preparation & Modelling Tasks as required - 10% Any other additional Input - Will not be considered for selection: Familiarity with Deep Learning Algorithms Image Processing & Classification Text Modelling using NLP Techniques Show more Show less

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do You will play an important role in applying and implementing effective machine learning solutions, with a significant focus on Generative AI. You will work with product and engineering teams to contribute to data-driven product strategies, explore and implement GenAI applications, and deliver impactful insights. This position is an individual contributor role reporting to the Senior Manager, Data Science. Responsibility Experiment with, apply, and implement DL/ML models, with a strong emphasis on Large Language Models (LLMs), Agentic Frameworks, and other Generative AI techniques to predict user behavior, enhance product features, and improve automation Utilize and adapt various GenAI techniques (e.g., prompt engineering, RAG, fine-tuning existing models) to derive actionable insights, generate content, or create novel user experiences Collaborate with product, engineering, and other teams (e.g., Sales, Marketing, Customer Success) to build Agentic system to run campaigns at-scale Conduct in-depth analysis of customer data, market trends, and user insights to inform the development and improvement of GenAI-powered solutions Partner with product teams to design, administer, and analyze the results of A/B and multivariate tests, particularly for GenAI-driven features Leverage data to develop actionable analytical insights & present findings, including the performance and potential of GenAI models, to stakeholders and team members Communicate models, frameworks (especially those related to GenAI), analysis, and insights effectively with stakeholders and business partners Stay updated on the latest advancements in Generative AI and propose their application to relevant business problems Complete assignments with a sense of urgency and purpose, identify and help resolve roadblocks, and collaborate with cross-functional team members on GenAI initiatives Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What you bring Basic Bachelor's or Master's degree in Computer Science, Physics, Mathematics, Statistics, or a related field 3+ years of hands-on experience in building data science applications and machine learning pipelines, with demonstrable experience in Generative AI projects Experience with Python for research and software development purposes, including common GenAI libraries and frameworks Strong knowledge of common machine learning, deep learning, and statistics frameworks and concepts, with a specific understanding of Large Language Models (LLMs), transformer architectures, and their applications Experience with or exposure to prompt engineering, and utilizing pre-trained LLMs (e.g., via APIs or open-source models) Experience with large datasets, distributed computing, and cloud computing platforms (e.g., AWS, Azure, GCP) Proficiency with relational databases (e.g., SQL) Experience in training, evaluating, and deploying machine learning models in production environments, with an interest in MLOps for GenAI Proven track record in contributing to ML/GenAI projects from ideation through to deployment and iteration Experience using machine learning and deep learning algorithms like CatBoost, XGBoost, LGBM, Feed Forward Networks for classification, regression, and clustering problems, and an understanding of how these can complement GenAI solutions Experience as a Data Scientist, ideally in the SaaS domain with some focus on AI-driven product features Preferred PhD in Statistics, Computer Science, or Engineering with specialization in machine learning, AI, or Statistics, with research or projects in Generative AI 5+ years of prior industry experience, with at least 1-2 years focused on GenAI applications Previous experience applying data science and GenAI techniques to customer success, product development, or user experience optimization Hands-on experience with fine-tuning LLMs or working with RAG methodologies Experience with or knowledge of experimentation platforms (like DataRobot) and other AI related ones (like CrewAI) Experience with or knowledge of the software development lifecycle/agile methodology, particularly in AI product development Experience with or knowledge of Github, JIRA/Confluence Contributions to open-source GenAI projects or a portfolio of GenAI related work Programming Languages like Python, SQL; familiarity with R Ability to break down complex technical concepts (including GenAI) into simple terms to present to diverse, technical, and non-technical audiences Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice Show more Show less

We is looking for a skilled Machine Learning Engineer with hands-on experience deploying models on Google Cloud Platform (GCP) using Vertex AI. This role involves enabling real-time and batch model inferencing based on specific business requirements, with a strong focus on production-grade ML deployments. Experience: 3 to 4 years Key Responsibilities: * Deploy machine learning models on GCP using Vertex AI. * Design and implement real-time and batch inference pipelines. * Monitor model performance, detect drift, and manage lifecycle. * Ensure adherence to model governance best practices and support ML-Ops workflows. * Collaborate with cross-functional teams to support Credit Risk, Marketing, and Customer Service use cases, especially within the retail banking domain. * Develop scalable and maintainable code in Python and SQL. * Work with diverse datasets, perform feature engineering, and build, train, and fine-tune advanced predictive models. * Contribute to model deployment in the lending space. Required Skills & Experience: * Strong expertise in Python and SQL. * Proficient with ML libraries and frameworks such as scikit-learn, pandas, NumPy, spaCy, CatBoost, etc. * In-depth knowledge of GCP Vertex AI and ML pipeline orchestration. * Experience with ML-Ops and model governance. * Exposure to use cases in retail banking—Credit Risk, Marketing, and Customer Service. * Experience working with structured and unstructured data. Nice to Have: * Prior experience deploying models in the lending domain. * Understanding of regulatory considerations in financial services. Job Type: Full-time Schedule: Day shift Work Location: In person

About ISOCRATES Since 2015, iSOCRATES advises on, builds and manages mission-critical Marketing, Advertising and Data technologies, platforms, and processes as the Global Leader in MADTECH Resource Planning and Execution(TM). iSOCRATES delivers globally proven, reliable, and affordable Strategy and Operations Consulting and Managed Services for marketers, agencies, publishers, and the data/tech providers that enable them. iSOCRATES is staffed 24/7/365 with its proven specialists who save partners money, and time and achieve transparent, accountable, performance while delivering extraordinary value. Savings stem from a low-cost, focused global delivery model at scale that benefits from continuous re-investment in technology and specialized training. About MADTECH.AI MADTECH.AI is the Unified Marketing, Advertising, and Data Decision Intelligence Platform purpose-built to deliver speed to value for marketers. At MADTECH.AI, we make real-time AI-driven insights accessible to everyone. Whether you’re a global or emerging brand, agency, publisher, or data/tech provider, we give you a single source of truth - so you can capture sharper insights that drive better marketing decisions faster and more affordable than ever before. MADTECH.AI unifies and transforms MADTECH data and centralizes decision intelligence in a single, affordable platform. Leave data wrangling, data model building, proactive problem solving, and data visualization to MADTECH.AI. Job Description We are seeking a highly skilled, results-oriented Product Manager - AI & BI to lead the growth and development of iSOCRATES' MADTECH.AI™ platform. As a core member of the product team, you will play an instrumental role in shaping the future of our AI-powered Marketing, Advertising, and Data Decision Intelligence solutions. Your focus will be on driving innovation in AI and BI capabilities, ensuring that our product meets the evolving needs of our B2B customers and enhances their marketing and data analytics capabilities. Key Responsibilities Product Strategy & Roadmap Development: Lead the creation and execution of the MADTECH.AI™ product roadmap, with a focus on incorporating AI and BI technologies to deliver value for B2B customers. Collaborate with internal stakeholders to define product features, prioritize enhancements, and ensure alignment with iSOCRATES’ long-term business objectives. AI & BI Product Development: Spearhead the design and development of innovative AI and BI features to enhance the MADTECH.AI™ platform’s scalability, functionality, and user experience. Leverage cutting-edge technologies such as machine learning, predictive analytics, natural language processing (NLP), data visualization, reinforcement learning, and other advanced AI techniques to deliver powerful marketing, advertising, and data decision intelligence solutions. Cross-Functional Collaboration: Collaborate with cross-functional teams, including engineering, design, marketing, sales, and customer success, to ensure seamless product development and delivery. Facilitate communication between technical and business teams to ensure product features align with customer needs and market trends. Customer & Market Insights: Engage with customers and other stakeholders to gather feedback, identify pain points, and stay on top of market trends. Use this data to shape product development and enhance MADTECH.AI™ capabilities, ensuring they are well-positioned in the evolving market landscape. Product Lifecycle Management: Oversee the complete product lifecycle from ideation through launch and beyond. Manage ongoing iterations of the product based on customer feedback and performance metrics to ensure that MADTECH.AI™ remains competitive and meets user expectations. Data-Driven Decision Making: Use customer analytics, usage patterns, and performance data to inform key product decisions. Define success metrics, monitor product performance, and make adjustments as needed to drive product success. AI/BI Thought Leadership: Stay current on the latest trends in AI, BI, MarTech, and AdTech. Act as a thought leader both internally and externally to position iSOCRATES as an innovator in the MADTECH.AI space. Promote best practices and contribute to the company’s overall strategy for AI and BI product development. Qualifications & Skills Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Business, or a related field. At least 12 years of experience in product management, with a minimum of 7 years focused on B2B SaaS solutions and strong expertise in AI and BI technologies. Prior experience in marketing, advertising, or data analytics platforms is highly preferred. AI & BI Expertise: Deep understanding of Artificial Intelligence, Machine Learning, Natural Language Processing (NLP), Predictive Analytics, Data Visualization, Business Intelligence tools (e.g., Tableau, Power BI, Qlik), and their application in SaaS products, especially within the context of MarTech, AdTech, or DataTech. AI Tools and Technologies : Hands-on experience with AI and BI tools such as: Data Science Libraries: TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM, Hugging Face Transformers, CatBoost, H2O.ai BI Platforms: Tableau, Power BI, Qlik, Looker, Domo, Sisense, MicroStrategy Machine Learning Tools: Azure ML, Google AI Platform, AWS Sagemaker, Databricks, H2O.ai, Vertex AI Data Analytics Tools: Apache Hadoop, Apache Spark, Apache Flink, SQL-based tools, dbt, Snowflake Data Visualization Tools: D3.js, Plotly, Matplotlib, Seaborn, Chart.js, Superset Cloud-Based AI Services: Google AI, AWS AI/ML services, IBM Watson, Microsoft Azure Cognitive Services, Oracle Cloud AI Emerging Tools: AutoML platforms, MLOps tools, Explainable AI (XAI) tools Product Development: Proven experience in leading AI/BI-driven product development within SaaS platforms, including managing the full product lifecycle, from ideation to launch and post-launch iterations. Agile Methodology: Experience working in Agile product development environments, with the ability to prioritize and manage multiple initiatives and product features simultaneously. Analytical & Data-Driven: Strong analytical skills with a focus on leveraging data, performance metrics, and customer feedback to inform product decisions. Ability to translate complex data into actionable insights. Customer-Centric: Experience in working directly with customers to understand their needs, pain points, and feedback. A customer-first mindset with a focus on building products that provide measurable value. Excellent Communication Skills: Exceptional communication, presentation, and interpersonal skills, with the ability to engage and influence both technical teams and business stakeholders across different geographies. Industry Knowledge: Familiarity with MADTECH.AI platforms and technologies. Understanding of customer journey analytics, predictive analytics, and decision intelligence platforms like MADTECH.AI™ is a plus. Cloud & SaaS Architecture: Familiarity with cloud-based solutions and large-scale SaaS architecture. Understanding of how AI and BI features integrate with cloud infrastructure is beneficial. Experience with AI-powered decision intelligence platforms like MADTECH.AI™ or similar MarTech, AdTech, or DataTech tools. In-depth knowledge of cloud technologies, including AWS, Azure, or Google Cloud, and their integration with SaaS platforms. Exposure to customer journey analytics, predictive analytics, and other advanced AI/BI tools. Willingness to work from Mysore/Bangalore or travel to Mysore as per business requirement. Show more Show less

ML Engineer | 3+ years | Remote | Work Timing: Standard IST Job Description: We are looking for a skilled Machine Learning Engineer with hands-on experience deploying models on Google Cloud Platform (GCP) using Vertex AI. This role involves enabling real-time and batch model inferencing based on specific business requirements, with a strong focus on production-grade ML deployments. Key Responsibilities: Deploy machine learning models on GCP using Vertex AI. Design and implement real-time and batch inference pipelines. Monitor model performance, detect drift, and manage lifecycle. Ensure adherence to model governance best practices and support ML-Ops workflows. Collaborate with cross-functional teams to support Credit Risk, Marketing, and Customer Service use cases, especially within the retail banking domain. Develop scalable and maintainable code in Python and SQL. Work with diverse datasets, perform feature engineering, and build, train, and fine-tune advanced predictive models. Contribute to model deployment in the lending space. Required Skills & Experience: Strong expertise in Python and SQL. Proficient with ML libraries and frameworks such as scikit-learn, pandas, NumPy, spaCy, CatBoost, etc. In-depth knowledge of GCP Vertex AI and ML pipeline orchestration. Experience with ML-Ops and model governance. Exposure to use cases in retail banking—Credit Risk, Marketing, and Customer Service. Experience working with structured and unstructured data. Nice to Have: Prior experience deploying models in the lending domain. Understanding of regulatory considerations in financial services. Job Type: Contractual / Temporary Contract length: 6 months Pay: ₹70,000.00 - ₹80,000.00 per month Benefits: Work from home Schedule: Monday to Friday Morning shift UK shift US shift Application Question(s): Are you ready to move Onsite | Bangalore/Pune? Education: Bachelor's (Preferred) Experience: ML Engineer: 3 years (Required)

Company Qualcomm India Private Limited Job Area Information Technology Group, Information Technology Group > IT Management General Summary Experience in engaging with business and technical stakeholders, understanding complex problem statements, and proposing value-driven Data Science & ML solutions Functional & technical leadership in developing data science roadmap and guiding the team with end-to-end delivery (design, development, maintenance, and optimization) of advanced analytical solutions with focus on process standardization and best practices Proactive in reaching out to wide variety of stakeholders for increasing the awareness of Data Science, ML and GenAI capabilities and identifying business value driven opportunities Analyze the market and industry trends in the technology and proactively look for opportunities in bringing the best solutions 'Strong analytical skills with the ability to gather information from several sources and identify fundamental patterns/trends in data Conduct research, design statistical studies and develop solutions Develop Story Telling dashboards on analytics to assist business in decision making Implement deep learning models for structured and unstructured data sets Perform Time Series Analysis and Forecast (ARIMA, Exponential Smoothing, VAR etc.) Implementation experience with identifying, prototyping, developing and delivering GenAI solutions using Industry standard RAG models and frameworks Ability to develop capabilities in Text Analytics ranging from Basic to Advanced (Topic Modelling, NLP) Experience with AWS suite of Data Science and ML tools Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, Catboost etc.) 'Experience With Other Cloud Platforms (GCP And Azure) Understanding of Data Platforms and Data Engineering Exposure to ChatBot solutions and Automation technologies Minimum Qualifications 7+ years of IT-related work experience with a Bachelor's degree. OR 9+ years of IT-related work experience without a Bachelor’s degree. 4+ years in a leadership role in projects/programs. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3067263 Show more Show less

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What You'll Do You will play an important role in applying and implementing effective machine learning solutions, with a significant focus on Generative AI. You will work with product and engineering teams to contribute to data-driven product strategies, explore and implement GenAI applications, and deliver impactful insights. This position is an individual contributor role reporting to the Senior Manager, Data Science. Responsibility Experiment with, apply, and implement DL/ML models, with a strong emphasis on Large Language Models (LLMs), Agentic Frameworks, and other Generative AI techniques to predict user behavior, enhance product features, and improve automation Utilize and adapt various GenAI techniques (e.g., prompt engineering, RAG, fine-tuning existing models) to derive actionable insights, generate content, or create novel user experiences Collaborate with product, engineering, and other teams (e.g., Sales, Marketing, Customer Success) to build Agentic system to run campaigns at-scale Conduct in-depth analysis of customer data, market trends, and user insights to inform the development and improvement of GenAI-powered solutions Partner with product teams to design, administer, and analyze the results of A/B and multivariate tests, particularly for GenAI-driven features Leverage data to develop actionable analytical insights & present findings, including the performance and potential of GenAI models, to stakeholders and team members Communicate models, frameworks (especially those related to GenAI), analysis, and insights effectively with stakeholders and business partners Stay updated on the latest advancements in Generative AI and propose their application to relevant business problems Complete assignments with a sense of urgency and purpose, identify and help resolve roadblocks, and collaborate with cross-functional team members on GenAI initiatives Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What You Bring Basic Bachelor's or Master's degree in Computer Science, Physics, Mathematics, Statistics, or a related field 3+ years of hands-on experience in building data science applications and machine learning pipelines, with demonstrable experience in Generative AI projects Experience with Python for research and software development purposes, including common GenAI libraries and frameworks Strong knowledge of common machine learning, deep learning, and statistics frameworks and concepts, with a specific understanding of Large Language Models (LLMs), transformer architectures, and their applications Experience with or exposure to prompt engineering, and utilizing pre-trained LLMs (e.g., via APIs or open-source models) Experience with large datasets, distributed computing, and cloud computing platforms (e.g., AWS, Azure, GCP) Proficiency with relational databases (e.g., SQL) Experience in training, evaluating, and deploying machine learning models in production environments, with an interest in MLOps for GenAI Proven track record in contributing to ML/GenAI projects from ideation through to deployment and iteration Experience using machine learning and deep learning algorithms like CatBoost, XGBoost, LGBM, Feed Forward Networks for classification, regression, and clustering problems, and an understanding of how these can complement GenAI solutions Experience as a Data Scientist, ideally in the SaaS domain with some focus on AI-driven product features Preferred PhD in Statistics, Computer Science, or Engineering with specialization in machine learning, AI, or Statistics, with research or projects in Generative AI 5+ years of prior industry experience, with at least 1-2 years focused on GenAI applications Previous experience applying data science and GenAI techniques to customer success, product development, or user experience optimization Hands-on experience with fine-tuning LLMs or working with RAG methodologies Experience with or knowledge of experimentation platforms (like DataRobot) and other AI related ones (like CrewAI) Experience with or knowledge of the software development lifecycle/agile methodology, particularly in AI product development Experience with or knowledge of Github, JIRA/Confluence Contributions to open-source GenAI projects or a portfolio of GenAI related work Programming Languages like Python, SQL; familiarity with R Ability to break down complex technical concepts (including GenAI) into simple terms to present to diverse, technical, and non-technical audiences Life At Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Our global benefits Paid time off Take time to unwind with earned days off, plus paid company holidays based on your region. Paid parental leave Take up to six months off with your child after birth, adoption or foster care placement. Full health benefits Options for 100% employer-paid health plans from day one of employment. Retirement plans Select retirement and pension programs with potential for employer contributions. Learning & development Grow your career with coaching, online courses and education reimbursements. Compassionate care leave Paid time off following the loss of a loved one and other life-changing events.