1487 Data Scientist Jobs - Page 5

Role Overview We are seeking a highly skilled Data Scientist with 4 to 8 years of experience to join our dynamic team. The ideal candidate will leverage expertise in Python, SQL, NLP, Computer Vision, Machine Learning, and PySpark to develop and implement advanced data solutions that support our clients’ digital transformation journeys. You will collaborate closely with business stakeholders and technical teams to analyze complex data sets and deliver actionable insights. Key Responsibilities Design, develop, and deploy machine learning models and data-driven solutions for clients in the financial services sector. Apply NLP and computer vision techniques to extract insights from unstructured data sources. Write optimized SQL queries to extract and manipulate large datasets from relational databases. Build scalable data pipelines and workflows using PySpark for large-scale data processing. Collaborate with cross-functional teams to translate business requirements into analytical solutions. Conduct exploratory data analysis to identify trends, patterns, and opportunities for improvement. Communicate findings and recommendations effectively to both technical and non-technical stakeholders. Stay current with emerging technologies and methodologies in data science, NLP, computer vision, and big data. Mandatory Skills Strong programming skills in Python for data science and machine learning. Proficient in SQL for complex data extraction and manipulation. Hands-on experience with Natural Language Processing (NLP) techniques and tools. Practical knowledge of Computer Vision algorithms and frameworks. Expertise in Machine Learning model development, evaluation, and deployment. Experience working with PySpark for big data processing and ETL workflows. Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field. 4+ years of professional experience as a Data Scientist or in a similar role. Strong analytical, problem-solving, and communication skills. Ability to work independently and as part of a collaborative team in a fast-paced environment. About Company: Capco, a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising of over 100 global organizations, Capco operates at the intersection of business and technology by combining innovative thinking with unrivalled industry knowledge to deliver end-to-end data-driven solutions and fast-track digital initiatives for banking and payments, capital markets, wealth and asset management, insurance, and the energy sector. Capcoâs cutting-edge ingenuity is brought to life through its Innovation Labs and award-winning Be Yourself At Work culture and diverse talent. Our approach is tailor-made to fit with each clientâs problem with an emphasis on building long-term strategic partnerships that foster collaboration and trust. We have the people, the vision, and the passion. Capco is committed to providing clients with practical solutions. We offer a globally integrated service with offices in leading financial centers across the Americas, Europe and Asia Pacific. Job Type: Full-time Work Location: In person

Evaluate model development data quality, methodology Perform proper documentation Conduct in-depth analysis of large data sets and support the review and maintenance process of relevant models and model validation documentation. Required Candidate profile 2+ years experience in model development or model validation experience in the retail section of a U. S. financial services/banking hands-on and proven experience utilizing Python, Spark , SAS, SQL,

Looking for Data Scientists (Generative AI) to Design, develop, and deploy GenAI applications to solve complex business problems. Integrate various LLM APIs into production systems. 2+ years of experience in Data Science Strong proficiency in Python

Role Overview As a Lead Data Scientist, youll optimize algorithms, lead a team, and develop cutting-edge solutions to improve our platforms performance. Collaborate across teams and stay at the forefront of AdTech advancements to drive measurable impact. Key Responsibilities Optimize and develop algorithms to enhance our DMP for OOH advertising. Lead a team of data scientists, ensuring project success and mentorship. Collaborate with cross-functional teams to identify and address challenges. Present data insights to technical and non-technical stakeholders. Ensure data quality, integrity, and compliance with privacy regulations. Requirements Masters/PhD in Data Science, Computer Science, or related field. 5+ years in data science with a focus on algorithm development. Expertise in machine learning, statistical modeling, and Python/Java. Proven leadership and excellent problem-solving skills. Strong communication skills; AdTech/OOH experience is a plus.

Job Summary Bluphlux is seeking a talented Data Scientist to join our innovative team. As a Data Scientist, you will play a crucial role in leveraging data to enhance our AI-driven recruitment solutions. You will work closely with our development team to refine our patented algorithms and ensure our clients receive the most accurate and efficient recruitment services. Key Responsibilities Develop and implement data models and algorithms to improve recruitment processes. Analyze large datasets to extract actionable insights and improve decision-making. Collaborate with cross-functional teams to integrate data-driven solutions into our recruitment platform. Continuously evaluate and improve the performance of our AI algorithms. Stay up-to-date with the latest advancements in data science and AI to ensure our solutions remain cutting-edge. Required Qualifications Bachelors or Masters degree in Data Science, Computer Science, Statistics, or a related field. Proven experience as a Data Scientist or similar role. Strong programming skills in Python, R, or similar languages. Experience with machine learning frameworks such as TensorFlow or PyTorch. Excellent analytical and problem-solving skills. Preferred Skills Experience in the recruitment or HR tech industry. Familiarity with natural language processing (NLP) techniques. Knowledge of cloud platforms such as AWS or Azure.

Senior Data Scientist Do you like working in collaborative teams and solving technical problems Are you a Senior Data Scientist looking for a new challenge Join our innovative Engineering Team! Our Industrial and Energy Technology (IET) operates across 120 countries, serving the entire energy value chain and the industrial sector. We hold an extensive portfolio of rotating equipment, process flow, transmission technology and lifecycle services. Our Engineering Transformation team works to improve the quality of our Engineering processes. Partner with the best As a Senior Data Scientist, you will collaborate within a data science or cross-functional team alongside partners at Baker Hughes. Key focus areas include Automatic Defect Recognition (ADR) and Remote Monitoring & Diagnostics (RM&D) in Non-Destructive Testing (NDT) industrial sectors. You will lead customer engagements and develop analytics aligned with business objectives to address specific needs and opportunities. As a Senior Data Scientist, you will be responsible for: Engaging with stakeholders to define analytical goals. Designing and implementing ML/computer vision models for industrial use cases. Developing reusable components for scalable solutions. Building defect detection models for visual, ultrasound, and CT/X-ray images. Using TensorFlow/PyTorch for image classification, detection, and segmentation. Applying transfer learning to enhance model performance. Building and deploying ML pipelines using Flask, FastAPI, Streamlit, Docker, etc. Using time series and predictive maintenance to forecast equipment failures. Deploying solutions on edge or cloud platforms. Documenting results in technical and validation reports. Fuel your passion To be successful in this role, you will: Have a Bachelors, Master s, or PhD in Computer Science or a STEM field, with 3+ years of experience in developing computer vision solutions for industrial applications. Have at least 4 years of hands-on experience with machine learning and computer vision algorithms for tasks such as object detection, recognition, tracking, and segmentation. Have proficiency in deep learning and ML libraries such as TensorFlow, PyTorch, Keras, scikit-learn, and OpenCV. Have good knowledge of Convolutional Networks and Deep Learning algorithms Have solid programming skills with Python and/or non-scripting languages Have experience in data cleansing, data quality assessment, and applying analytics on industrial datasets Have practical knowledge of time series analysis and predictive maintenance for forecasting equipment health and optimising maintenance. Have good communication skills to collaborate with stakeholders and explain technical concepts to non-technical audiences. Have experience with Docker containers & cloud deployment is a plus Have prior exposure to NDT inspection data (e.g., CT/X-ray images) is a plus. Work in a way that works for you We recognise that everyone is different and that the way in which people want to work and deliver at their best is different for everyone too. In this role, we can offer the following flexible working patterns: Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive Working with us Our people are at the heart of what we do at Baker Hughes. We know we are better when all of our people are developed, engaged and able to bring their whole authentic selves to work. We invest in the health and well-being of our workforce, train and reward talent and develop leaders at all levels to bring out the best in each other. Working for you Our inventions have revolutionised energy for over a century. But to keep going forward tomorrow, we know we have to push the boundaries today. We prioritise rewarding those who embrace change with a package that reflects how much we value their input. Join us, and you can expect: Contemporary work-life balance policies and wellbeing activities Comprehensive private medical care options Safety net of life insurance and disability programs Tailored financial programs Additional elected or voluntary benefits

Senior Data Scientist Do you like working in collaborative teams and solving technical problems Are you a Senior Data Scientist looking for a new challenge Join our innovative Engineering Team! Our Industrial and Energy Technology (IET) operates across 120 countries, serving the entire energy value chain and the industrial sector. We hold an extensive portfolio of rotating equipment, process flow, transmission technology and lifecycle services. Our Engineering Transformation team works to improve the quality of our Engineering processes. Partner with the best As a Senior Data Scientist, you will collaborate within a data science or cross-functional team alongside partners at Baker Hughes. Key focus areas include Automatic Defect Recognition (ADR) and Remote Monitoring & Diagnostics (RM&D) in Non-Destructive Testing (NDT) industrial sectors. You will lead customer engagements and develop analytics aligned with business objectives to address specific needs and opportunities. As a Senior Data Scientist, you will be responsible for: Engaging with stakeholders to define analytical goals. Designing and implementing ML/computer vision models for industrial use cases. Developing reusable components for scalable solutions. Building defect detection models for visual, ultrasound, and CT/X-ray images. Using TensorFlow/PyTorch for image classification, detection, and segmentation. Applying transfer learning to enhance model performance. Building and deploying ML pipelines using Flask, FastAPI, Streamlit, Docker, etc. Using time series and predictive maintenance to forecast equipment failures. Deploying solutions on edge or cloud platforms. Documenting results in technical and validation reports. Fuel your passion To be successful in this role, you will: Have a Bachelors, Master s, or PhD in Computer Science or a STEM field, with 3+ years of experience in developing computer vision solutions for industrial applications. Have at least 4 years of hands-on experience with machine learning and computer vision algorithms for tasks such as object detection, recognition, tracking, and segmentation. Have proficiency in deep learning and ML libraries such as TensorFlow, PyTorch, Keras, scikit-learn, and OpenCV. Have good knowledge of Convolutional Networks and Deep Learning algorithms Have solid programming skills with Python and/or non-scripting languages Have experience in data cleansing, data quality assessment, and applying analytics on industrial datasets Have practical knowledge of time series analysis and predictive maintenance for forecasting equipment health and optimising maintenance. Have good communication skills to collaborate with stakeholders and explain technical concepts to non-technical audiences. Have experience with Docker containers & cloud deployment is a plus Have prior exposure to NDT inspection data (e.g., CT/X-ray images) is a plus. Work in a way that works for you We recognise that everyone is different and that the way in which people want to work and deliver at their best is different for everyone too. In this role, we can offer the following flexible working patterns: Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive Working with us Our people are at the heart of what we do at Baker Hughes. We know we are better when all of our people are developed, engaged and able to bring their whole authentic selves to work. We invest in the health and well-being of our workforce, train and reward talent and develop leaders at all levels to bring out the best in each other. Working for you Our inventions have revolutionised energy for over a century. But to keep going forward tomorrow, we know we have to push the boundaries today. We prioritise rewarding those who embrace change with a package that reflects how much we value their input. Join us, and you can expect: Contemporary work-life balance policies and wellbeing activities Comprehensive private medical care options Safety net of life insurance and disability programs Tailored financial programs Additional elected or voluntary benefits

Our client, an investment firm, is looking to expand its systematic strategies platform and is hiring a Senior Quantitative Researcher in Bangalore, India. Key Responsibilities: Quantitative Research & Model Development: Design, build, and enhance statistical and machine learning models to forecast market behavior and identify trading opportunities. Advanced Data Analytics: Extract insights from large-scale historical and alternative datasets to develop predictive signals and evaluate strategy performance. Strategy Design & Deployment: Partner with trading and engineering teams to backtest strategies using proprietary platforms and support live deployment in production environments. Algorithmic Optimization: Continuously refine models and algorithms to improve execution efficiency, predictive accuracy, and robustness across various market conditions. Risk & Scalability Assessment: Conduct thorough risk evaluations of models and strategies, including stress testing and analysis of scalability constraints. Tooling & Infrastructure: Develop and maintain research tools and dashboards to support simulation, visualization, and performance tracking of trading strategies. Cross-functional Collaboration: Engage closely with developers, traders, and portfolio managers to align research goals with business objectives and ensure successful strategy implementation. Key Requirements 5+ years of hands-on quantitative research experience with a proven record of live deployment. Hold a Bachelors, Masters, or PhD in Mathematics, Statistics, Physics, Computer Science, Engineering, or Financial Engineering from a top-tier institute. Proficient in programming languages like Python, R, or C++. Experience in Indian Markets and MFT. Experience with MFT strategies in Delta 1 and Options, particularly arbitrage or market making.

Description We are seeking a highly skilled and motivated Data Scientist with expertise in leveraging data to inform business strategy and drive product innovations. In this role, you will apply your expertise in machine learning and analytics. As Data Scientist you will play a crucial role in developing and implementing innovative solutions that leverage AI/ML platform to extract valuable insights from complex data sets. Your work will contribute to enhancing our data-driven decision-making processes and advancing our products and services. Responsibilities: Improve the performance of RCM processes by building and launching machine learning models such as insurance eligibility prediction Design, execute, and analyze A/B testing experiments to measure model performance and validate product hypotheses Define metrics and create dashboards to measure product performance Generate insights through deep-dive analysis to inform strategy and prioritization Collaborate with product, engineering, and marketing stakeholders to define the product roadmap Identify opportunities and initiate new data science projects that drive company OKRs Communicate technical insights effectively to influence decision-making Qualifications You have a Master s degree in a relevant quantitative field (e.g. data science , computer science, statistics, economics) or equivalent in industry experience You have 5-8 years of experience as a data scientist supporting product development You are an expert in SQL You are proficient in either R or Python for data analysis You have successfully developed and launched ML models with quantifiable business impact You have experience designing and analyzing A/B testing experiments and guide product decisions with experimental insights You are results-driven and passionate about building great products, with a proven track record of taking projects from inception to launch Job Information Technology Primary Location India-Karnataka-Bengaluru Schedule: Full-time Travel: No Req ID: 251423 Job Hire Type Experienced Not Applicable #BMI N/A

About Team The Myntra Data Science team is at the forefront of innovation, delivering cutting-edge solutions that drive significant revenue and enhance customer experiences across various touchpoints. Every quarter, our models impact millions of customers, leveraging real-time, near-real-time, and offline solutions with diverse latency requirements. These models are built on massive datasets, allowing for deep learning and growth opportunities within a rapidly expanding organization. By joining our team, youll gain hands-on experience with an extensive e-commerce platform, learning to develop models that handle millions of requests per second with sub-second latency. We take pride in deploying solutions that not only utilize state-of-the-art machine learning techniques such as graph neural networks, diffusion models, transformers, representation learning, optimization methods, and Bayesian modeling but also contribute to the research community with multiple peer-reviewed publications. Roles and Responsibilities Design, Develop, and Deploy: Create and implement advanced machine learning models and algorithms to tackle complex business challenges across various domains, including Recommender Systems, Search, Computer Vision, Supply Chain Management (SCM), Pricing, Forecasting, Trend and Virality Prediction, Generative AI, and more. Technical Expertise: Demonstrate deep theoretical knowledge and practical expertise in one or more areas, such as Natural Language Processing (NLP), Computer Vision, Recommender Systems, Gen AI and Optimization. Software Development: Develop robust, scalable, and maintainable software solutions for seamless model deployment. CI/CD Pipelines: Set up and manage Continuous Integration/Continuous Deployment (CI/CD) pipelines for automated testing, deployment, and model integration. Model Maintenance: Maintain and optimize machine learning pipelines, including data cleaning, feature extraction, and model training. Collaboration: Work closely with the Platforms and Engineering teams to ensure smooth deployment and integration of ML models into production systems. Data Management: Partner with the Data Platforms team to gather, process, and analyze data crucial for model development. Code Quality: Write clean, efficient, and maintainable code following best practices. Performance Optimization: Conduct performance testing, troubleshooting, and tuning to ensure optimal model performance. Continuous Learning: Stay up-to-date with the latest advancements in machine learning and technology, sharing insights and knowledge across the organization. Qualifications Experience Industry Experience: 3-5+ years with a Bachelors degree, or 2+ years with a Master s/Ph.D. in Computer Science, Mathematics, Statistics, or a related field. Machine Learning Expertise: At least 2 years of hands-on experience as a Machine Learning Engineer or a similar role. Production Deployment: Proven experience deploying machine learning solutions into production environments. Programming Skills: Strong proficiency in Python or equivalent programming languages for model development. ML Frameworks: Familiarity with leading machine learning frameworks (Keras, TensorFlow, PyTorch) and libraries (scikit-learn). CI/CD Tools: Experience with CI/CD tools and practices. Communication: Excellent verbal and written communication skills. Teamwork Independence: Ability to work collaboratively in a team environment or independently as needed. Workload Management: Strong organizational skills to manage and prioritize tasks, supporting your manager effectively. Exceptional candidates are encouraged to apply, even if you dont meet every listed qualification. Were open to hiring individuals who demonstrate outstanding potential. Nice to Have Research Contributions: Publications or presentations in recognized Machine Learning and Data Science journals/conferences. Big Data Technologies: Experience with big data technologies like Spark or other distributed computing frameworks. Cloud Services: Proficiency in cloud platforms (AWS, Google Cloud) and an understanding of distributed systems. Generative AI Exposure: Familiarity with Generative AI models. Database Management: Experience with SQL and/or NoSQL databases. ML Orchestration: Knowledge of ML orchestration tools (Airflow, Kubeflow, MLFlow). " Who are we Myntra is India s leading fashion and lifestyle platform, where technology meets creativity. As pioneers in fashion e-commerce, we ve always believed in disrupting the ordinary. We thrive on a shared passion for fashion, a drive to innovate to lead, and an environment that empowers each one of us to pave our own way. We re bold in our thinking, agile in our execution, and collaborative in spirit. Here, we create MAGIC by inspiring vibrant and joyous self-expression and expanding fashion possibilities for India, while staying true to what we believe in. We believe in taking bold bets and changing the fashion landscape of India. We are a company that is constantly evolving into newer and better forms and we look for people who are ready to evolve with us. From our humble beginnings as a customization company in 2007 to being technology and fashion pioneers today, Myntra is going places and we want you to take part in this journey with us. Working at Myntra is challenging but fun - we are a young and dynamic team, firm believers in meritocracy, believe in equal opportunity, encourage intellectual curiosity and empower our teams with the right tools, space, and opportunities.

We are seeking a motivated Data Scientist with a strong foundation in statistics and 1-3 years of relevant experience to join our dynamic team. As a key member of our data analytics group, you will assist in analysing data, developing models, and deriving insights to drive strategic decision-making. Key Responsibilities: Analyse large datasets to identify trends, patterns, and insights. Apply statistical methods to solve business problems and inform decision-making. Develop predictive models using machine learning techniques. Assist in data cleaning, preparation, and exploratory data analysis. Collaborate with cross-functional teams to understand data needs and provide actionable insights. Present findings and recommendations to stakeholders in a clear and concise manner. Stay updated with the latest trends in data science, statistical methodologies, and large language models (LLMs). Qualifications: Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, or a related field. Minimum 1-3 years of experience in data analysis, statistical modelling, or machine learning projects. Strong understanding of statistical concepts and methodologies. Familiarity with programming languages such as Python or R. Basic knowledge of large language models (LLMs) and their applications. Experience with data visualization tools (e.g., Tableau, Power BI) is a plus. Basic knowledge of machine learning algorithms and techniques. Strong analytical and problem-solving skills. Excellent communication and teamwork abilities. What We Offer: Opportunity to work on real-world data science projects. Mentorship and training from experienced data scientists. A collaborative and innovative work environment. Opportunities for professional growth and development. Job Types: Full-time, Permanent Pay: ₹40,000.00 - ₹50,000.00 per month Benefits: Paid sick time Paid time off Schedule: Day shift Morning shift Work Location: In person

Growexx is looking for a smart and passionate Data Scientist , who will empower Marketing, Product, and Sales teams to make strategic, data-driven decisions. Key Responsibilities Mine, process, and analyze web, product, sales, and digital marketing data at an event level. Utilize traditional machine learning techniques and language models (LLMs) to build great AI agents for different business needs. Assist in developing and optimizing LLM-driven solutions for tasks such as text summarization and basic customer support automation. Contribute to building and deploying predictive models and machine learning algorithms across customer profile and usage datasets. Support the deployment of machine learning models into production environments. Assist in designing and implementing basic model activation strategies and participating in A/B testing plans. Conduct evaluations of LLMs, focusing on basic performance metrics like accuracy and latency. Integrate LLM agents with APIs and assist in maintaining data models and improving taxonomy. Key Skills Hands on experience with LLM models and basic knowledge of evaluation metrics for LLMs. Knowledge of designing and deploying agentic systems. knowledge bases, retrieval systems (RAG architecture), and orchestrating dynamic multi-agent workflows. Exposure to machine learning techniques including supervised and unsupervised learning Proficiency in Python, SciKit, SQL, Jupyter Notebooks and understanding of cloud platforms for data science tasks. Basic understanding of data mining and statistical analysis techniques. Continuous learner, keeping up-to-date with the latest advances in transformers, generative AI models, retrieval-augmented generation (RAG), and agentic AI frameworks. Education and Experience B Tech or B. E. (Computer Science / Information Technology) 1+ years as a Data Scientist or similar roles. Analytical and Personal skills Must have good logical reasoning and analytical skills. Good Communication skills in English – both written and verbal. Demonstrate Ownership and Accountability of their work. Attention to detail.

What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

Join our Team About this opportunity We are now looking for a Senior Data Scientist to be responsible for developing AI/ML methods, processes, and systems to extract knowledge or insights to drive the future of artificial intelligence!! Provide data science tasks, perform advanced statistical analysis, and create insights into data to provide to the business actionable insights, identify trends, and measure performance which address business problems. Collaborate with business and process owners to understand business issues, and with engineers to implement and deploy scalable solutions, where applicable!! What you will do Apply and/or develop statistical modeling techniques (such as deep neural networks, Bayesian models, Generative AI, Forecasting), optimization methods and other ML techniques. Synthesize problems into data question(s). Convert data into practical insights. Analyze and investigate data quality for identified data and communicate it Product Owner, Business Analyst, and other relevant stakeholders. Collect Data, explore it, and perform analysis to extract information suitable to the business need. Identify gaps in the data, aggregate data as per business need. Design & perform Data Analysis, Data Validation, Data Transformation, Feature Extraction. Decide approach for addressing business needs with Data & analytics. Understand end user needs and work accordingly with identifying new features in the data. Develop Data Science and Engineering Infrastructure &Tools. Derive key metrics suitable for the use-case and present the analysis to key stakeholder. You will bring 4-8 years of relevant Industry experience. A Bachelor’s or higher degree in Computer Science, Statistics, Mathematics, or related disciplines. Ability to analyse data and communicate outcome to key stakeholders exploring new data source Excellent coding skills in python, R, SQL etc. Understanding of cloud services. Evidence of academic training in Statistics. Deep/broad knowledge of machine learning, statistics, optimization, or related field A genuine curiosity about new and applied technology and software engineering coupled with a high degree of business understanding. Experience in large scale product development is a plus. Experience in Generative AI and Large Language Models Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more. Primary country and city: India (IN) || Kolkata Req ID: 768998

Job Description for Data Scientist Preferred Experience : 5-7 years Work Location: Kolkata About RS Software RS Software builds global, national and enterprise payment platforms, and has presence in four continents. The product suite combines with knowledge systems built over 30 years, delivering mission-critical payment solutions that combine innovation and entrepreneurship to create the new gold standard for digital payments. With approximately 40% of the global digital payment volumes in 2021 processed on platforms built by RS Software, the vision is to deliver Payments at the Speed of Thought . RS Software is focused on the global payments modernization market, providing large-scale, high-performance payment systems, serving central Infrastructures, financial institutions, payment network providers, payment processors and software companies providing products to the payment industry. The company's product suite offers ISO 20022 ready, open payments architecture using a cloud-based microservices framework - optimizing costs, seamless integrations with commoditized products, and accelerates the pace of adoption. The company’s solutions today are installed in 12 of the top 20 banks in India, and the four major platforms built by RS Software cumulatively process annually 350+ billion transactions world-wide, giving the company a rare track record in the payments domain. RS Software’s product suite is getting recognized in some important markets, which is creating strategic partnerships, the foundation for the company’s long-term growth. RS Software has bult India’s digital payment infrastructure, the three major payment platforms, which are transforming the lives of a billion+ people. Instant digital payment platform (UPI) Bill payment platform - Bharat Bill Payment System (BBPS) Enterprise Fraud and Risk Management (EFRM) Why RS Software? RS provides a unique experience of engaging in some world class product development and prestigious large scale payment platforms that caters to billions of people We provide opportunity to learn and develop high throughput transaction processing systems RS Software is one of the few technology and payment solutions providers where talented individuals have the opportunity to work on cutting-edge, complex, and mission-critical IT projects. We offer ample career opportunities to hardworking and skilled employees Our Talent Management Program is specifically designed to identify the interests of each employee and match them with suitable career paths within their desired domains, allowing them to make the best possible use of their skillsets in reaching their goals We invest in the knowledge and skill development of our employees with RS School of Payments – the industry’s most comprehensive training platform. There are three main areas of focus that the Academy and School address: current technology skills, professional development and payments domain knowledge Our customized training program, well-defined career mapping process and comprehensive appraisal system is designed to help every employee achieve their goals To address the challenges of relocation, we offer employees coming from other regions reimbursement for expenses associated with their moves as well as complimentary interim facilities, such as guesthouse accommodations, to ease the transition. We also assist employees with finding suitable housing Role Overview: We are seeking a talented and driven Data Scientist to join our team and contribute to the development of advanced analytics solutions, including fraud detection, stream analytics, and predictive modelling. The ideal candidate will have 3-5 years of hands-on experience designing and deploying machine learning models and a passion for uncovering insights from data. In this role, you will collaborate with cross-functional teams, including engineering, product, and data science, to create and optimize data pipelines, develop innovative analytics models, and enhance our understanding of complex patterns in digital payments and beyond. Familiarity with digital payments, fraud detection, Gen AI, and real-time data processing is a strong advantage. Key Responsibilities : Develop and deploy machine learning models for fraud detection, stream analytics, and predictive use cases Create and maintain data pipelines to support machine learning model development Analyse transaction data to identify patterns and deviations that indicate potential fraud Design and implement models to analyse and predict behaviours in the digital payments domain Collaborate with cross-functional teams to streamline user workflows using Generative AI (Gen AI) Develop a comprehensive dashboard for real-time monitoring of fraud patterns and model performance Enhance and maintain the model studio, enabling business users to train and deploy models autonomously Work on end-to-end machine learning pipelines to bring models to production, ensuring scalability and performance Required Skills : Proficiency in SQL for data manipulation and understanding relational database concepts (e.g., MySQL, PostgreSQL) Ability to integrate and consume data using REST APIs, with familiarity in API best practices and testing Skilled in Python for data analysis, machine learning, and API interaction, with experience in libraries like Pandas, NumPy, and Scikit-learn Hands-on experience designing, developing, and deploying machine learning models for fraud detection, stream analytics or predictive use cases Strong proficiency in data analysis, feature engineering, and model optimization techniques Working knowledge of Java and SpringBoot for model integration Strong understanding of digital payment systems, fraud patterns, and risk analysis Experience working with Gen AI to improve workflows and user experiences Ability to work on large datasets and create scalable data pipelines Excellent communication skills and a proactive, problem-solving mindset Ability to work in a collaborative team environment and take initiative on projects Preferred Skills : Exposure to fraud detection algorithms and techniques used in the digital payments industry Experience working with cloud technologies such as AWS. Azure, GCP is not mandatory but a plus Knowledge of data visualization and dashboard tools for reporting model performance If you’re passionate about AI/ML and working on impactful real-time payment systems, we would love to hear from you!

We are looking for 5+years experienced candidates for this role. Job Description Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Responsibilities include: Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Have expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Expertise in GenAI models is a must. Design, implement, and optimize data pipelines for model training and deployment. Experience with any one of the model serving frameworks (e.g.,TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Primary Skills : Python Data Science concepts Generative AI Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision Predictive Analytics Time Series Analysis Anomaly Detection Recommendation Systems SQL Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP)

ONLY IMMEDIATE JOINERS: Role & responsibilities Design, train, and deliver data science solutions using all modalities (tabular, text, image) Working hands on advanced analytics projects using python Mentor and work with a team of data scientists and data engineer to build advanced analytical solutions for clients Analyse experimental results, iterate, and refine models to create significant business impact Understanding and formulating the business problem into analytics framework Managing stakeholders, and communicating insights to business and technical teams Preferred candidate profile Mandatory: Time Series Forecasting, Demand Forecasting, Python, Pricing Analytics Customer and Marketing Analytics Pricing and Promotion Analytics Supply Chain Analytics Demand Forecasting / Production Planning / Procurement / Inventory Planning / Logistics Digital Analytics Predictive Maintenance / Predictive Quality In-depth understanding of various machine learning algorithms Ability to write robust codes in Python and familiarity with standard machine learning libraries is a plus Excellent communication and interpersonal skills to interact with internal and external stakeholders Good team player, self-motivated, able to ideate and work on various initiatives Perks and benefits

About the job Position: Assistant Manager/Manager Credit Risk What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

Data Scientist Bengaluru/Chennai (Hybrid also possible) This is fast moving position with our client need immediate joiner. Job Description Looking for Data scientists with product analytics and technically skills, hands on development experience in Python, statistical techniques, SQL and basic Data visualization with lot of attention to granular details in data., Self-motivated, team player, with curiosity to learn and grow, exhibiting strong resolve and challenge the status quo, to strive for excellence in everything they do, with good professional and academic track record to be part of a team that deals with most innovative payments processing team that deals transactions at scale. Candidate Requirements Top must-have skills SQL Python Tableau Statistics AB Testing Your way to impact What do you need to bring- Strong 4+ Years of experience in Python and SQL skills with a lot of attention to granular details in data Expertise in stitching together findings to convey coherent insights with statistical significance and analysis Use A/B Testing, analytics, market research, usability studies, and competitive analysis to drive decision making. Exceptional oral and written communication skills Ability to perform deep dive analyses on key business trends from multiple perspectives and package the insights into easily consumable presentations and documents Engage in problem solving with the product and various merchant facing teams to determine performance trends and root causes. Support new product launches for merchants by ensuring constant monitoring is in place to track product performance. Partner with varies internal teams to ensure that the merchants analytic needs are well addressed. Create close relationships with stakeholders to anticipate & answer the questions that might be asked both by internal and external parties. Degrees or certifications required.

About The Position We are looking for a dynamic and experienced Data Scientist to join our growing AI & Data Science team. In this role, you will lead projects and collaborate with cross-functional teams to build and deploy cutting-edge machine learning solutions that drive business value. Technical and Professional Requirements Minimum 5+ years of experience in data science, with at least 2 years in a leadership or team management role. Proficiency in Natural Language Processing (NLP) techniques such as LDA, embeddings, Retrieval-Augmented Generation (RAG). Experience in time series forecasting, statistical modeling, and predictive analytics. Hands-on experience with Databricks, Azure ML stack, Python, and Django. Solid understanding of end-to-end data science workflows, from data engineering to model deployment. Ability to collaborate across diverse teams and communicate technical concepts clearly to stakeholders. Job Responsibilities Build and deploy end-to-end ML pipelines, including data preprocessing, model training, and production deployment. Implement supervised, unsupervised, and deep learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Collaborate with data scientists and engineers to integrate ML models into production systems. Use MLOps tools like MLflow or Kubeflow for CI/CD and model lifecycle management. Monitor and optimize deployed models for performance and scalability. Stay updated on ML advancements and contribute to innovation within the team. Educational Requirements: Minimum 60% in any two of the following: Secondary Higher Secondary Graduation.

Roles and Responsibilities: As a, Data scientist / Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve predefined outcomes. Engage with clients to understand current and future business goals and translate business problems into analytical frameworks Develop custom models based on in-depth understanding of underlying data, data structures, and business problems to ensure deliverables meet client needs Create repeatable, interpretable and scalable models Effectively communicate the analytics approach and insights to a larger business audience Collaborate with team members, peers and leadership at Tredence and client companies Qualification: Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience. 3+ years of experience in data science, building hands-on ML models Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. Experience leading the end-to-end design, development, and deployment of predictive modeling solutions. Excellent programming skills in Python. Strong working knowledge of Python’s numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc. Advanced SQL skills with SQL Server and Spark experience. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms (Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks Experience with Natural Language Processing (NLTK) and text analytics for information extraction, parsing and topic modeling. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills. Thrive in a fast-paced, innovative environment Experience with data visualization tools — PowerBI, Tableau, R Shiny, etc. preferred Experience with cloud platforms such as Azure, AWS is preferred but not require

Role: Data Scientist Experience: 4+ years Budget: 22 lpa Key Responsibilities: Develop AI-driven dashboards and reporting tools (Power BI, Tableau) Integrate ML/NLP models into business intelligence platforms Analyze data to deliver predictive/prescriptive insights Collaborate with cross-functional teams and support data infrastructure Must-Have Skills: Proficiency in Python/R/SQL Experience with ML frameworks (TensorFlow, PyTorch) Strong knowledge of NLP and GenAI applications Familiarity with cloud platforms (Azure preferred)

About Us: At Valiance, we empower businesses with AI-driven insights and data analytics solutions. Specializing in demand forecasting within retail Industry very specific to Apparel and Footwear domains, we leverage standardized ML models to deliver accurate forecasting outcomes to our clients. We are looking for a skilled Data Scientist who can interpret and improve these models to drive real-world business results. Role Overview: The Data Scientist will be responsible for applying our pre-trained demand forecasting models to generate actionable insights and highly accurate forecasting outcomes. This role involves thorough data analysis, identifying trends and anomalies, interpreting results, and communicating findings effectively to a non-technical business audience. The ideal candidate is less focused on creating algorithms and more oriented towards solving business challenges and providing insights that make a tangible impact. Key Responsibilities: Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and anomalies in demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have) Model Utilization: Leverage existing pre-trained forecasting models, optimizing their performance by incorporating a nuanced understanding of data points and improving model outcomes based on data insights. Interpretation & Communication: Interpret model results and explain outcomes in simple, actionable terms for business stakeholders, ensuring clarity and relevance. Insights Generation: Develop insights that guide business decisions, aiming for highly accurate forecasting outcomes to meet business requirements. Collaboration: Work closely with cross-functional teams, including business stakeholders and analysts, to ensure forecasting outputs align with business objectives and provide real-world value. Continuous Improvement: Identify opportunities to improve model performance through better data usage and fine-tuning, rather than new model development. Required Skills & Qualifications: Experience: 3-6 years of experience in data science or a related field, specifically in Demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have) Technical Proficiency: Strong skills in data analysis, data visualization, and working with pre-trained ML models. Proficiency in Python, and SQL is preferred. Business Focus: Strong orientation towards solving business problems rather than a pure focus on machine learning algorithms. Communication Skills: Ability to clearly communicate insights and forecast results to non-technical stakeholders in simple, understandable language. Problem Solving: Demonstrated ability to interpret data, uncover actionable insights, and suggest practical solutions for business needs. Detail-Oriented: Thorough attention to detail, ensuring accuracy in forecasting and relevance of insights. Educational Background: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.

What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.