6505 Machine Learning Jobs

Job Title: Assistant Manager - Learning designer (AI/ML) Location: HSR, Bangalore (Work from office) Experience Required: Minimum 4 years Department: Product Innovation Employment Type: Full-time Role Overview: We are looking for a passionate AI/ML Subject Matter Expert with a strong background in Artificial Intelligence, Machine Learning, Python, and Deep Learning to support our course development initiatives. As an SME, you will collaborate with the content, instructional design, and product teams to create high-quality, industry-relevant learning content. Key Responsibilities: Research and stay updated on emerging trends, tools, and technologies in AI/ML, Python, Deep Learning, and Data Science. Contribute to designing, reviewing, and refining Simplilearns AI/ML curriculum and learning paths. Create and validate course content including learning objectives, project ideas, assessments, and use cases. Work closely with instructional designers to ensure technical accuracy and pedagogical effectiveness. Support the content production team with scripting, reviewing, and storyboarding. Participate in webinars, doubt sessions, and learner engagement activities when required. Guide the integration of industry use-cases and capstone projects to enhance learner outcomes. Required Skills and Qualifications: Minimum 4 years of hands-on experience in AI/ML and related technologies. Proficiency in Python, with experience in libraries like NumPy, Pandas, Scikit-learn, TensorFlow, Keras, or PyTorch. Strong understanding of machine learning algorithms, data preprocessing, deep learning models, and NLP. Good analytical and communication skills. Experience in curriculum development or content creation is a strong plus. Exposure to e-learning, edtech, or training is desirable. Nice to Have: Published work, blogs, or GitHub projects in AI/ML. Experience with LLMs, GenAI, or RAG frameworks. Prior instructional design or teaching experience. Exposure in effectively lead and manage a team by allocating tasks based on individual strengths and capabilities to ensure optimal performance and successful project delivery.

Perform manual user access review and access control matrix review periodically. Reconciliation, validation of data, rectification of observations before sharing them with any auditors Publish periodic dashboards about review and ongoing audit updates to management Execute and deliver automation projects end to end Face various internal and external auditors. Provide evidence, data, and resolution on observations and process improvement to avoid further observations A team player with good communication skills Proficient in excel and power-point Adaptive in learning new skills Python knowledge will be added advantage

JOb Responsibilities: The Data Scientists will leverage expertise in advanced statistical and modelling techniques to design, prototype, and build the next-generation analytics engines and services. They will work closely with the analytics teams and business teams to derive actionable insights, helping the organization in achieving its’ strategic goals. Their work will involve high levels of interaction with the integrated analytics team, including data engineers, translators, and more senior data scientists. Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation Lead teams of 2-3 associate data scientists in the use case building and delivery process Can communicate complex technical concepts to both technical and non-technical audience Plays a key role in driving ideation around the modelling process and developing models. Can conceptualize and drive re-iteration and fine tuning of models Contribute to knowledge building and sharing by researching best practices, documenting solutions, and continuously iterating on new ways to solve problems. Mentors junior team members to do the same REQUIRED EDUCATION AND EXPERIENCE: Master’s degree in Computer Science, Statistics, Math, Operations Research, Economics, or a related field Advanced level programming skills in at least 1 coding language (R/Python/Scala) Practical experience of developing advanced statistical and machine learning models At least 2 years of relevant analytics experience Experience in using large database systems preferred Has developed niche expertise in at least one functional domain REQUIRED SKILLS: Ability to work well in agile environments in diverse teams with multiple stakeholders Experience of leading small teams Able to problem solve complex problems and break them down into simpler parts Ability to effectively communicate complex analytical and technical content High energy and passionate individual who can work closely with other team members Strong entrepreneurial drive to test new out of the box techniques Able to prioritize workstreams and adopt an agile approach Willing to adopt an iterative approach; experimental mindset to drive innovation LOCATION: Bangalore What’s in it for you ? Disruptive projects : Work on ‘ breakthrough’ digital-and-analytics projects to enable UPL’s vision of building a future ready organization. It involves deploy ing solutions to help us increase our sales, sustain our profitability, improve our speed to market, supercharge our R&D efforts, and support the way we work internally. Help us ensure we have access to the best business insights that our data analysis can offer us. Cross functional leadership exposure : Work directly under guidance of functional leadership at UPL, on the most critical business problems for the organization (and the industry) today. It will give you exposure to a large cross-functional team (e.g.: spanning manufacturing, procurement, commercial, quality, IT/OT experts), allowing multi-functional learning in D&A deployment Environment fostering professional and personal development : Strengthen professional learning in a highly impact-oriented and meritocratic environment that is focused on delivering disproportionate business value through innovative solutions. It will be supported by on-the-job coaching from experienced domain experts, and continuous feedback from a highly motivated and capable set of peers. Comprehensive training programs for continuous development through UPL's D&A academy will help in accelerating growth opportunities. Come join us in this transformational journey! Let’s collectively Change the game with Digital & Analytics!

Shift: (GMT+05:30) Asia/Kolkata (IST) What do you need for this opportunity? Must have skills required: Python, Golang, Rust, GCP, Airflow, Docker, Containerization, Hadoop, Hive, SQL, Spark, Generative AI, Agentic Workflows, Machine learning (ML) About the job Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their team's hybrid work schedule requirements. We are seeking an experienced Senior Machine Learning Manager to lead the Notifications Science team, focused on building intelligent, ML-driven systems for personalized notifications. These systems ensure that we send the right message to the right customer, at the right time, through the right channel (Push, Email, SMS), and at the right cadence, while balancing incremental revenue with customer engagement health. In this role, youll be accountable for the technical roadmap, driving innovation to build the next generation of Wayfairs communications ML stack. Youll work closely with a high-performing team of ML scientists and engineers to solve some of Wayfairs most complex challenges in personalization, latency, and scale with direct impact on customer experience and company revenue. What Youll do: Own the strategy, roadmap, and execution of notification intelligence and automation solutions. Lead the development of GenAI-powered content generation, send-time optimization, and cross-channel orchestration systems. Build intelligent systems that drive significant incremental revenue while minimizing customer fatigue and unsubscribes. Develop and grow technical leadership within the team, modeling a culture of continuous research and innovation. Collaborate with Engineering and Product teams to scale decisioning systems to millions of notifications daily. Act as a subject matter expert, providing mentorship and technical guidance across the broader Data Science and Engineering organization. We Are a Match Because You Have: Bachelor's or Masters degree in Computer Science, Mathematics, Statistics, or related field. 9+ years of industry experience, with at least 12 years of experience managing teams, and 5+ years as an individual contributor working on production ML systems. Strategic thinker with a customer-centric mindset and a desire for creative problem-solving, looking to make a big impact in a growing organization. Demonstrated success influencing senior-level stakeholders on strategic direction, based on recommendations backed by in-depth analysis, and excellent written and verbal communication skills. Ability to partner cross-functionally to own and shape technical roadmaps and the organizations required to drive them. Proficient in one or more programming languages, e.g., Python, Golang, or Rust. Nice to have: Experience with GCP, Airflow, and containerization (Docker). Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc. Experience in Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning. Familiarity with Generative AI and agentic workflows.

Shift: (GMT+05:30) Asia/Kolkata (IST) What do you need for this opportunity? Must have skills required: Machine Learning, NumPy, Data Cleaning, Python, Model evaluation, pandas, Statistics We are seeking a talented Data Scientist II to join our team. The ideal candidate will have 2-5 years of experience in data science and possess expertise in machine learning, deep learning, Python programming, SQL, Amazon Redshift, NLP, and AWS Cloud. ** Duties and Responsibilities: Develop and implement machine learning models to extract insights from large datasets. Utilize deep learning techniques to enhance data analysis and predictive modeling. Write efficient Python code to manipulate and analyze data. - Work with SQL databases to extract and transform data for analysis. Utilize Amazon Redshift for data warehousing and analytics. Apply NLP techniques to extract valuable information from unstructured data. - Utilize AWS Cloud services for data storage, processing, and analysis. Qualifications and Requirements: Bachelor's degree in Computer Science, Statistics, Mathematics, or related field. - 3-5 years of experience in data science or related field. Proficiency in machine learning, deep learning, Python programming, SQL, Amazon Redshift, NLP, and AWS Cloud. Strong analytical and problem-solving skills. - Excellent communication and teamwork abilities. * *Key Competencies - Strong analytical skills. - Problem-solving abilities. - Proficiency in machine learning and deep learning techniques. Excellent programming skills in Python. - Knowledge of SQL and database management. - Familiarity with Amazon Redshift, NLP, and AWS Cloud services. ** Performance Expectations: Develop and deploy advanced machine learning models. Extract valuable insights from complex datasets. Collaborate with cross-functional teams to drive data-driven decision-making. Stay updated on the latest trends and technologies in data science. We are looking for a motivated and skilled Data Scientist I to join our team and contribute to our data-driven initiatives. If you meet the qualifications and are passionate about data science, we encourage you to apply.

JOb Responsibilities: The Data Scientists will leverage expertise in advanced statistical and modelling techniques to design, prototype, and build the next-generation analytics engines and services. They will work closely with the analytics teams and business teams to derive actionable insights, helping the organization in achieving its’ strategic goals. Their work will involve high levels of interaction with the integrated analytics team, including data engineers, translators, and more senior data scientists. Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation Lead teams of 2-3 associate data scientists in the use case building and delivery process Can communicate complex technical concepts to both technical and non-technical audience Plays a key role in driving ideation around the modelling process and developing models. Can conceptualize and drive re-iteration and fine tuning of models Contribute to knowledge building and sharing by researching best practices, documenting solutions, and continuously iterating on new ways to solve problems. Mentors junior team members to do the same REQUIRED EDUCATION AND EXPERIENCE: Master’s degree in Computer Science, Statistics, Math, Operations Research, Economics, or a related field Advanced level programming skills in at least 1 coding language (R/Python/Scala) Practical experience of developing advanced statistical and machine learning models At least 2 years of relevant analytics experience Experience in using large database systems preferred Has developed niche expertise in at least one functional domain REQUIRED SKILLS: Ability to work well in agile environments in diverse teams with multiple stakeholders Experience of leading small teams Able to problem solve complex problems and break them down into simpler parts Ability to effectively communicate complex analytical and technical content High energy and passionate individual who can work closely with other team members Strong entrepreneurial drive to test new out of the box techniques Able to prioritize workstreams and adopt an agile approach Willing to adopt an iterative approach; experimental mindset to drive innovation

Shift: (GMT+05:30) Asia/Kolkata (IST) What do you need for this opportunity? Must have skills required: Machine Learning, ML, ml architectures and lifecycle, Airflow, Kubeflow, MLFlow, Spark, Kubernetes, Docker, Python, SQL, machine learning platforms, BigQuery, GCS, Dataproc, AI Platform, Search Ranking, Deep Learning, Deep Learning Frameworks, PyTorch, TensorFlow About the job Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their team's hybrid work schedule requirements. Who We Are Wayfairs Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques. What youll do Provide technical leadership in the development of an automated and intelligent advertising system by advancing the state-of-the-art in machine learning techniques to support recommendations for Ads campaigns and other optimizations. Design, build, deploy and refine extensible, reusable, large-scale, and real-world platforms that optimize our ads experience. Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped machine learning solutions Collaborate closely with various engineering, infrastructure, and machine learning platform teams to ensure adoption of best-practices in how we build and deploy scalable machine learning services Identify new opportunities and insights from the data (where can the models be improved? What is the projected ROI of a proposed modification?) Research new developments in advertising, sort and recommendations research and open-source packages, and incorporate them into our internal packages and systems. Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on. We Are a Match Because You Have: Bachelor's or Masters degree in Computer Science, Mathematics, Statistics, or related field. 6-9 years of industry experience in advanced machine learning and statistical modeling, including hands-on designing and building production models at scale. Strong theoretical understanding of statistical models such as regression, clustering and machine learning algorithms such as decision trees, neural networks, etc. Familiarity with machine learning model development frameworks, machine learning orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Kubernetes, Docker, Python, and SQL. Proficiency in Python or one other high-level programming language Solid hands-on expertise deploying machine learning solutions into production Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity Nice to have Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks). Experience in computational advertising, bidding algorithms, or search ranking Experience with deep learning frameworks like PyTorch, Tensorflow, etc.

Job Title: Senior Data Scientist Intelligent Offer Management Location: Bangalore (3 days work from office) Type: Full-time(On-Site) Experience Level: 3–6 years About the Role: We are hiring a Data Scientist to lead and scale our Intelligent Offer Management engine – a key pillar of our revenue optimisation strategy. This role sits at the intersection of data science, pricing strategy, product thinking, and experimentation, enabling personalised, dynamic, and contextual offer decisions at scale. You'll work closely with product managers, business teams, and engineers to build models that recommend the right offer to the right customer at the right time. Key Responsibilities -Design and implement real-time offer recommendation models using historical purchase, engagement, and behavioural data. - Develop algorithms for dynamic pricing, offer personalisation, segmentation, and discount optimisation. - Collaborate with cross-functional stakeholders to translate business requirements into data science solutions. - Conduct A/B and multivariate experiments to evaluate offer performance and optimise offer strategies. - Build predictive models for conversion propensity, elasticity curves, and uplift measurement. - Package models for production deployment, ensuring scalability, performance, and monitoring. - Influence product design and customer journeys with data-driven insights. Must-Have Qualifications: - 3-6 years of experience in data science, quantitative analytics, or pricing strategy roles. - Proficiency in Python and SQL, with experience in building, validating, and deploying ML models. - Deep understanding of offer science, pricing elasticity, behavioural economics, and incentive systems. - Strong business acumen with the ability to balance accuracy with impact and speed. - Experience working with experimentation frameworks and statistical inference. - Ability to communicate complex insights effectively to both technical and non-technical stakeholders.

Were looking for a Python-based AI/ML Developer who brings solid hands-on experience in building machine learning models and deploying them into scalable, production-ready APIs using FastAPI or Django. The ideal candidate is both analytical and implementation-savvy, capable of transforming models into live services and integrating them with real-world systems. Key Responsibilities Design, train, and evaluate machine learning models (classification, regression, clustering, etc.) Build and deploy scalable REST APIs for model serving using FastAPI or Django Collaborate with data scientists, backend developers, and DevOps to integrate models into production systems Develop clean, modular, and optimized Python code using best practices Perform data preprocessing, feature engineering, and data visualization using Pandas , NumPy , Matplotlib , and Seaborn Implement model serialization techniques (Pickle, Joblib, ONNX) and deploy models using containers (Docker) Manage API security with JWT and OAuth mechanisms Participate in Agile development with code reviews, Git workflows, CI/CD pipelines Must-Have Skills Python & Development Proficient in Python 3.x, OOP, and clean code principles Experience with Git, Docker, debugging, unit testing AI/ML Good grasp of supervised/unsupervised learning, model evaluation, and data wrangling Hands-on with Scikit-learn , XGBoost , LightGBM Web Frameworks FastAPI : API routes, async programming, Pydantic, JWT Django : REST Framework, ORM, Admin panel, Middleware DevOps & Cloud Experience with containerized deployment using Docker Exposure to cloud platforms: AWS , Azure , or GCP CI/CD with GitHub Actions, Jenkins, or GitLab CI Databases SQL: PostgreSQL, MySQL NoSQL: MongoDB, Redis ORM: Django ORM, SQLAlchemy Bonus/Nice-to-Have Skills Model tracking/versioning tools (MLflow, DVC) Knowledge of LLMs , transformers, vector DBs (Pinecone, Faiss) Airflow, Prefect, or other workflow automation tools Basic frontend skills (HTML, JavaScript, React) Requirements Education : B.E./B.Tech or M.E./M.Tech in Computer Science, Data Science, or related fields Experience : 36 years of industry experience in ML development and backend API integration Strong communication skills and ability to work with cross-functional teams Role & responsibilities

Role : AI / ML Engineer Experience : 5 to 9 Years Location : Bengaluru / Gurgaon / Chennai Primary Skills : AI/ML, Python Design and develop applications using Java/ Vertx & Reactive framework and Python. • Plan, scope, size, architect, design, prototype and engineer framework components. • CI/CD Implementation: Implement and manage Continuous Integration and Continuous Deployment (CI/CD) processes. • A problem solver, open to learning. Should have experience in troubleshooting, optimizing, solutioning and keeping up with evolving technologies - as a leading member of the team. • Work closely with product managers and stakeholders to understand business requirements and translate them into technical solutions. • Collaborate with software engineers to integrate OOTB services into existing servicing applications and ensure scalability and reliability. • Stay abreast of industry best practices and emerging trends in Python and Natural Language Processing. • Participate in cross-functional team meetings, brainstorming sessions, and knowledge sharing activities to foster innovation and continuous improvement. • Working in Agile Environments: Experience with Agile methodologies and practices. • Create and develop NLP systems by using the requirements set out for the project. • Use well-formed and effective text representation to change and adapt natural language into user-friendly features. • Research and implement the correct algorithms and tools for natural language processing tasks. • Experience in RDBMS and NoSQL databases such as Oracle, MSSQL, PostgreSQL, MongoDB, Casandra. • Develop and implement AI/ML Applications using Java and/or Python and leading industry tools and frameworks.

Hiring a Solution Architect with 810 yrs experience in data, AI & GenAI. Must have strong cloud (AWS/Azure/GCP), LLM, ML (TensorFlow/PyTorch), and full-stack skills. Role involves designing scalable architectures and leading technical teams.

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference.

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/ Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference.

Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 4- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 5- Have worked across end to end in model design, development, validation, documentation & deployment. 6- Create great data stories with expertise in robust EDA and statistical inference

Role Synopsis This role is a senior-level position within a data science team, responsible for providing leadership, strategic direction, and technical expertise in the field of data science and machine learning. This role involves leading all aspects of and guiding a team of data scientists while collaborating closely with multi functional departments, such as engineering, product management, and business collaborators. The Lead Data Scientist plays a pivotal role in crafting data-driven strategies and solutions that chip in to the organization's success and growth Key Accountabilities Data Analysis and Modeling: Lead data scientists must have a confirmed foundation in data analysis and a deep understanding of various machine learning algorithms They should be able to apply these techniques to address sophisticated problems and extract valuable insights from data Out of Code computing: Use libraries that support out-of-core computing, such as Dask in Python These libraries can process data that doesn't fit into memory by reading it in smaller portions from disk Business Insight: Understanding the FDO's business objectives and aligning data initiatives with them Project Management: Being skilled in project management methodologies helps in planning and driving data science projects efficiently Machine Learning: Innovation and Strategy - Advanced Machine Learning Skills for complex models. Evaluation Collaboration and Communication: Effective communication with collaborators, Explain the modeling approach and results. Implement to privacy guidelines and recommendation with conscious balance Continuous Learning: Staying up-to-date in competitive edge. Apply methodologies to practical business challenges. Meeting with domain GPO's Data cleaning and preprocessing, analysis: The ability to clean and preprocess data effectively is a fundamental skill in any data science role Data Ethics and Privacy: Open communication with customer. Ethical considerations in algorithm design. Secure data handling, Data minimization Database Management: Proficient in database systems and SQL is required for data retrieval and storage Domain knowledge: Expertise in the domain they are working in to understand the context and requirements of the data projects better Statistical Analysis and Mathematics: Solid grasp of statistical methods and mathematical concepts is needed for data analysis, modeling, and drawing substantial insights from data Experience and Job Requirements Data Science Team plays a crucial role in driving data-informed decision-making and generating actionable insights to support the company's goals. This team is responsible for processing, analyzing, and interpreting large and complex datasets from multiple datasets to provide valuable insights and recommendations across various domains. Through advanced analytical techniques and machine learning models, the data science team helps optimize processes, predict trends, and build data-driven strategies. A bachelor's or equivalent experience or master's degree in quantitative, qualitative field such as Computer Science, Statistics, Mathematics, Physics, Engineering, or a related data field is often required Skills: Leadership role in Data Analysis, Programming proficiency in Python, SQL, Azure Databricks, Statistics & Mathematics. Leadership qualities to steer the team. Strategic direction and technical expertise Soft skills: Active listening, Translate business problems into data questions, Communication and collaboration, Presentation, Problem solving, Multi-functional, Team management, Partner management Data Sources: SAP, Concur, Salesforce, Workday, Excel files Other: Project management. Domain knowledge [Procurement, Finance, Customer], Business Insight, Critical thinking, Story telling Able to prepare analytical reports, presentations and/or visualisation dashboards to communicate findings, important metrics and insights to both technical and non-technical customers Stay up to date with industry trends, standard methodologies and new technologies in data analytics, machine learning, data science techniques.

Job Summary We are looking for an experienced Data Scientist with 3 to 5 years of hands-on experience in building and deploying machine learning and natural language processing (NLP) models. The ideal candidate should have a solid foundation in AI, strong problem-solving abilities, and a passion for applying ML/NLP techniques to solve real-world challenges. Experience in designing AI agents or working with LLMs is a strong advantage. Key Responsibilities Develop, train, and deploy machine learning and NLP models to support business and product goals. Conduct end-to-end model lifecycle management, including feature engineering, model selection, evaluation, and optimization. Perform exploratory data analysis (EDA), hypothesis testing, and derive actionable insights. Design and build AI agents and workflows that interact with LLMs and integrate into larger systems. Collaborate with cross-functional teams including product, engineering, and design to deliver AI-driven solutions. Stay updated with advancements in GenAI, LLMs, and emerging trends in the AI ecosystem. Required Qualifications Bachelors or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 3–5 years of experience in applied machine learning, NLP, or AI model development. Proficiency in Python and commonly used data science libraries (e.g., Pandas, NumPy, Scikit-learn, Transformers). Hands-on experience with NLP frameworks (e.g., Hugging Face, spaCy) and model fine-tuning. Strong understanding of supervised/unsupervised learning, vectorization techniques, and evaluation metrics. Excellent problem-solving, communication, and collaboration skills. Preferred Qualifications Experience working with large language models (LLMs) and vector databases. Exposure to building AI agents, autonomous workflows, or prompt engineering. Familiarity with cloud platforms (e.g., AWS) and scalable ML infrastructure. Understanding of MLOps practices for model deployment and monitoring.

Dear Candidate, We are seeking a Machine Learning Engineer to develop predictive models and deploy them into production. Ideal for professionals passionate about AI and data science. Key Responsibilities: Develop and train machine learning models Preprocess and analyze large datasets Deploy models using scalable infrastructure Collaborate with product teams to integrate ML solutions Required Skills & Qualifications: Strong knowledge of Python and ML libraries (scikit-learn, TensorFlow, PyTorch) Experience with data preprocessing and feature engineering Familiarity with model deployment techniques Bonus: Experience with cloud ML services (AWS SageMaker, Google AI Platform) Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

Data Scientist 2-Digital Banking Kotak 811-Regional Sales Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 4- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 5- Have worked across end to end in model design, development, validation, documentation & deployment. 6- Create great data stories with expertise in robust EDA and statistical inference

Role & responsibilities You should be someone who thrives on solving complex problems and has a natural attraction to ill-defined challenges that seem intractable, transforming them into elegant data science solutions. You find yourself comfortable in the middle of what seems to be chaos, knowing you can discover patterns and create order through data. You want to create a meaningful impact by solving complex healthcare problems through your passion for data science and machine learning. Advanced degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field 5+ years of hands-on data science experience with a proven track record of deploying ML models to production Expert-level proficiency in SQL and Python , with extensive experience using standard Python machine learning libraries (scikit-learn, pandas, numpy, matplotlib, seaborn, etc.) Cloud platform experience, preferably AWS, with hands-on knowledge of SageMaker, S3, Redshift, and Jupyter Notebook workbenches (other cloud environments acceptable) Strong statistical modeling and machine learning expertise across supervised and unsupervised learning techniques Experience with model deployment, monitoring, and MLOps practices Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders Preferred candidate profile

Overview We are seeking an experienced Sustainability & Climate TPM to lead the execution of a comprehensive sustainability and climate strategy, ensuring alignment with the company’s goals. This role will oversee the implementation of sustainability and climate initiatives across the business. Responsibilities Primary responsibilities include: Coordinating with relevant stakeholders to drive projects and ensure timely delivery with high quality Ensuring roadmaps and action plans are in place to mitigate risks and projects are run with a commercial and client centric approach Establishing structures and processes to follow up on the execution of roadmaps and action plans and report on status to senior management. Drive automation of reporting and jira updates. Finding effective solutions together with the business and shared services to meet client needs around regulation and investment decisions Staying up to date about future trends, market requirements, regulations, AI and best AI practices to drive efficiency, scale and innovation. Qualifications Domain knowledge of Sustainability & Climate Technical /Data background preferable Excellent Communication and Stakeholder management skills Ability to prirotize and manage risks What we offer you Transparent compensation schemes and comprehensive employee benefits, tailored to your location, ensuring your financial security, health, and overall wellbeing. Flexible working arrangements, advanced technology, and collaborative workspaces. A culture of high performance and innovation where we experiment with new ideas and take responsibility for achieving results. A global network of talented colleagues, who inspire, support, and share their expertise to innovate and deliver for our clients. Global Orientation program to kickstart your journey, followed by access to our Learning@MSCI platform, LinkedIn Learning Pro and tailored learning opportunities for ongoing skills development. Multi-directional career paths that offer professional growth and development through new challenges, internal mobility and expanded roles. We actively nurture an environment that builds a sense of inclusion belonging and connection, including eight Employee Resource Groups. All Abilities, Asian Support Network, Black Leadership Network, Climate Action Network, Hola! MSCI, Pride & Allies, Women in Tech, and Women’s Leadership Forum. At MSCI we are passionate about what we do, and we are inspired by our purpose – to power better investment decisions. You’ll be part of an industry-leading network of creative, curious, and entrepreneurial pioneers. This is a space where you can challenge yourself, set new standards and perform beyond expectations for yourself, our clients, and our industry. MSCI is a leading provider of critical decision support tools and services for the global investment community. With over 50 years of expertise in research, data, and technology, we power better investment decisions by enabling clients to understand and analyze key drivers of risk and return and confidently build more effective portfolios. We create industry-leading research-enhanced solutions that clients use to gain insight into and improve transparency across the investment process. MSCI Inc. is an equal opportunity employer. It is the policy of the firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, gender, gender identity, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy (including unlawful discrimination on the basis of a legally protected parental leave), veteran status, or any other characteristic protected by law. MSCI is also committed to working with and providing reasonable accommodations to individuals with disabilities. If you are an individual with a disability and would like to request a reasonable accommodation for any part of the application process, please email Disability.Assistance@msci.com and indicate the specifics of the assistance needed. Please note, this e-mail is intended only for individuals who are requesting a reasonable workplace accommodation; it is not intended for other inquiries. To all recruitment agencies MSCI does not accept unsolicited CVs/Resumes. Please do not forward CVs/Resumes to any MSCI employee, location, or website. MSCI is not responsible for any fees related to unsolicited CVs/Resumes. Note on recruitment scams We are aware of recruitment scams where fraudsters impersonating MSCI personnel may try and elicit personal information from job seekers. Read our full note on careers.msci.com

Familiarity in programming patterns in Python. Exposure to Kafka, RabbitMQ, or AWS EventBridg, Data science exposure. Built or contributed to agentic systems, ML/AI pipelines, or intelligent automation tools. Understanding of MLOps Food allowance Health insurance Provident fund

Roles and Responsibilities : Design, develop, test, and deploy NLP models using Python and machine learning algorithms. Collaborate with cross-functional teams to integrate NLP solutions into existing systems. Develop data pipelines for large-scale text analysis and sentiment analysis projects. Troubleshoot issues related to model performance, data quality, and system integration. Job Requirements : 3-8 years of experience in natural language processing (NLP) development using Python. Strong understanding of machine learning concepts and techniques. Proficiency in developing scalable data pipelines for big data processing. Experience with popular NLP libraries such as NLTK, spaCy, or Hugging Face Transformers.

Global Gen AI Developer Enabling a software-defined, electrified future. Visteon is a technology company that develops and builds innovative digital cockpit and electrification products at the leading-edge of the mobility revolution. Founded in 2000, Visteon brings decades of automotive intelligence combined with Silicon Valley speed to apply global insights that help transform the software-defined vehicle of the future for many of the worlds largest OEMs. The company employs 10,000 employees in 18 countries around the globe. To know more about us click here. Mission of the Role: Facilitate Enterprise machine learning and artificial intelligence solutions using the latest technologies Visteon is adopting globally. Key Objectives of this Role: The primary goal of the Global ML/AI Developer is to leverage advanced machine learning and artificial intelligence techniques to develop innovative solutions that drive Visteons strategic initiatives. By collaborating with cross-functional teams and stakeholders, this role identifies opportunities for AI-driven improvements, designs and implements scalable ML models, and integrates these models into existing systems to enhance operational efficiency. Following development best practices, fostering a culture of continuous learning, and staying abreast of AI advancements, the Global ML/AI Developer ensures that all AI solutions align with organizational goals, support data-driven decision-making, and continuously improve Visteons technological capabilities. Qualification, Experience and Skills: 6-8 Yrs Technical Skills: Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, R, SQL), and data processing tools (e.g., Apache Spark, Hadoop). Proficiency in developing, training, and deploying ML models, including supervised and unsupervised learning, deep learning, and reinforcement learning. Strong understanding of data engineering concepts, including data preprocessing, feature engineering, and data pipeline development. Experience with cloud platforms (preferably Microsoft Azure) for deploying and scaling ML solutions. Business Acumen : Strong business analysis and ability to translate complex technical concepts into actionable business insights and recommendations. Key Behaviors: Innovation: Continuously seeks out new ideas, technologies, and methodologies to improve AI/ML solutions and drive the organization forward. Attention to Detail: Pays close attention to all aspects of the work, ensuring accuracy and thoroughness in data analysis, model development, and documentation. Effective Communication: Clearly and effectively communicates complex technical concepts to non-technical stakeholders, ensuring understanding and alignment across the organization.

The Data Scientist-3 in Bangalore (or Mumbai) will be part of the 811 Data Strategy Group that comprises Data Engineers, Data Scientists and Data Analytics professionals. He/she will be associated with one of the key functional areas such as Product Strategy, Cross Sell, Asset Risk, Fraud Risk, Customer Experience etc. and help build robust and scalable solutions that are deployed for real time or near real time consumption and integrated into our proprietary Customer Data Platform (CDP). This is an exciting opportunity to work on data driven analytical solutions and have a profound influence on the growth trajectory of a super fast evolving digital product. Key Requirements of The Role - Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 7 - 10 Years of relevant experience in the space Expertise in mining AI/ML opportunities from open ended business problems and drive solution design/development while closely collaborating with engineering, product and business teams Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets. Strong experience in NLP, time series forecasting and recommendation engines preferred Create great data stories with expertise in robust EDA and statistical inference. Should have at least a foundational understanding in Experimentation design Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. Exposure to Deep Learning applications and tools like TensorFlow, Theano, Torch, Caffe preferred Experience with analytical programming languages, tools and libraries (Python a must) as well as Shell scripting. Should be proficient in developing production ready code as per best practices. Experience in using Scala/Java/Go based libraries a big plus Very proficient is SQL and other relational databases along with PySpark or Spark SQL. Proficient is using NoSQL databases. Experience in using GraphDBs like Neo4j a plus. Candidate should be able to handle unstructured data with ease. Candidate should have experience in working with MLEs and be proficient (with experience) in using MLOps tools. Should be able to consume the capabilities of said tools with deep understanding of deployment lifecycle. Experience in CI/CD deployment is a big plus. Knowledge of key concepts in distributed systems like replication, serialization, concurrency control etc. a big plus Good understanding of programming best practices and building code artifacts for reuse. Should be comfortable with version controlling and collaborate comfortably in tools like git Ability to create frameworks that can perform model RCAs using analytical and interpretability tools. Should be able to peer review model documentations/code bases and find opportunities Experience in end-to-end delivery of AI driven Solutions (Deep learning , traditional data science projects) Strong communication, partnership and teamwork skills Should be able to guide and mentor teams while leading them by example. Should be an integral part of creating a team culture focused on driving collaboration, technical expertise and partnerships with other teams Ability to work in an extremely fast paced environment, meet deadlines, and perform at high standards with limited supervision A self-starter who is looking to build grounds up and contribute to the making of a potential big name in the space Experience in Banking and financial services is a plus. However, sound logical reasoning and first principles problem solving are even more critical A typical day in the life of the job role: 1. As a key partner at the table, attend key meetings with the business team to bring in the data perspective to the discussions 2. Perform comprehensive data explorations around to generate inquisitive insights and scope out the problem 3. Develop simplistic to advanced solutions to address the problem at hand. We believe in making swift (albeit sometimes marginal) impact to business KPIs and hence adopt an MVP approach to solution development 4. Build re-usable code analytical frameworks to address commonly occurring business questions 5. Perform 360-degree customer profiling and opportunity analyses to guide new product strategy. This is a nascent business and hence opportunities to guide business strategy are plenty 6. Guide team members on data science and analytics best practices to help them overcome bottlenecks and challenges 7. The role will be an approximate 60% IC 40% leading and the ratios can vary basis need and fit 8. Develop Customer-360 Features that will be integrated into the Customer Data Platform (CDP) to enhance the single view of our customer .

Experience: 4+ years of hands-on experience in deploying and monitoring machine learning models. Basic understanding of ML and data science/modeling aspects. Experience with open-source tools for MLOps, such as Kubernetes, Docker, and Apache Airflow and developing and streamlining workflows, building scalable pipelines, etc. Ensuring successful model development, testing, optimization, scaling, monitoring/observability, and governance Continuous integration and continuous deployment (CI/CD) Proficiency in cloud platforms, especially Azure and/or AWS. Strong scripting skills (e.g., Python) for automation and tool development. Problem-Solving: o Strong problem-solving skills with a focus on finding efficient and scalable solutions. o Ability to learn new tools on the go and developing best practices is mandatory.