8,613 Data Science Manager jobs in India

This role is for one of worko's clients, a leading E-commerce platform:

About the role

Are you a strategic thinker with a passion for solving large-scale problems using data? Do you enjoy mentoring high-performing teams and building ML systems that directly impact millions of users? We're looking for a Data Science Manager to lead a team of skilled data scientists in building intelligent systems that power our client's next phase of growth.

In this role, you’ll own the data science roadmap for a key business charter, guiding the team through ambiguity and complexity to deliver production-grade ML solutions. You’ll work closely with product, tech, and business leaders to translate complex challenges into scalable, measurable, and impactful outcomes. As a people and technical leader, you’ll ensure model efficiency, system reliability, and scientific excellence while fostering a culture of innovation, collaboration, and continuous improvement.

Key Responsibilities

• Lead, grow, and mentor a high-performing team of data scientists and ML engineers.
• Own all data science systems and models in your charter — from strategy to deployment and monitoring.
• Collaborate with senior product, engineering, and business leaders to define and prioritize impactful DS initiatives.
• Drive platformization, system architecture decisions, and ML lifecycle improvements across the charter.
• Ensure model scalability, performance, and cost efficiency, while upholding best practices in experimentation and statistical rigor.
• Guide the team in reading and implementing state-of-the-art research, and facilitate build vs. buy decisions.
• Lead RCA for critical production issues and improve system observability, documentation, and service uptime.

Requirements

• Master’s degree (PhD preferred) in Machine Learning, Statistics, Computer Science, or a related quantitative field.
• 8+ years of experience in Data Science or Analytics, with at least 2–3 years of people management experience.
• Proven track record of building and deploying ML models in production at scale.
• Experience managing teams of 4+ data scientists/engineers and delivering across cross-functional charters.
• Deep expertise in ML algorithms, experimental design, and performance monitoring.
• Strong coding skills (Python, SQL) and familiarity with Big Data technologies like Spark, Hive, or Redshift.
• Ability to translate business needs into technical solutions, prioritize roadmaps, and estimate effort accurately.
• Strong communication and stakeholder management skills with a bias for action and clarity in execution.

Mandatory Requirements

• Master’s degree in Machine Learning, Statistics, Computer Science, or related quantitative field
• 8+ years of experience in Data Science or Analytics
• 2–3 years of people management experience
• Proven track record of building and deploying ML models in production at scale
• Experience managing teams of 4+ data scientists/engineers
• Deep expertise in ML algorithms, experimental design, and performance monitoring
• Strong coding skills (Python, SQL)
• Familiarity with Big Data technologies like Spark, Hive, or Redshift
• Ability to translate business needs into technical solutions
• Strong communication and stakeholder management skills

Preferred Requirements

• Experience leading ML initiatives in B2C or e-commerce settings
• Contributions to internal tools, open-source libraries, or research publications
• Experience in personalization, recommendations, ranking, or supply chain ML problems
• Strong understanding of ML system performance trade-offs

Salary

100-120 lpa

Godrej Capital is a subsidiary of Godrej Industries and is the holding company for Godrej Housing finance & Godrej Finance. With a digital-first approach and a keen focus on customer-centric product innovation, Godrej Capital offers Home Loans, Loan Against Property, Property Loans, Business Loans and is positioned to diversify into other customer segments and launch new products. The company is focused on building a long-term, sustainable retail financial services business in India, anchored by Godrej Group’s 125+year legacy of trust and excellence. Godrej Capital has a special focus on learning and capability development across its employee base and is committed to diversity, equity, and inclusion as a guiding principle.

The organization has been consistently recognized as a Great Place to WorkTM receiving certifications in 2022 and 2023. As it stands, Godrej Capital holds a spot among India's Top 50 Best Workplaces in BFSI 2023 and is also recognized as one of India’s Great Mid-Size Workplaces 2023. Beyond that, it has also had the honor of being named the Best Organization for Women by The Economic Times in both 2022 and 2023, and the Best Workplaces for Women by Great Place to Work in 2022 and in 2023.

About the Role:

As a key member of the Modeling Center of Excellence at Godrej Capital, you will drive data-driven initiatives that empower strategic business decisions through model building and implementation. Your expertise will contribute to developing advanced analytical models, optimizing credit risk processes, and implementing innovative solutions that enhance the company's lending operations.

Key Responsibilities:

• Design, develop, and deploy machine learning models and analytical algorithms to support credit risk assessment, behavioral scoring, collection prioritization, customer propensity modeling, and other critical lending decisions.
• Analyze complex datasets to identify patterns, trends, and emerging risks, delivering actionable insights through models that inform business strategies and early warning systems.
• Collaborate closely with technology teams to enhance data infrastructure and optimize business workflows, ensuring seamless integration and production deployment of scalable ML models.
• Lead, mentor, and guide a team of junior analysts and data scientists in delivering high-quality, impactful analytical frameworks and models.
• Explore and incorporate alternative data sources and innovative data-driven techniques to uncover new opportunities and refine credit risk for improved portfolio performance.

Qualifications & Experience:

• 5 to 7 years of professional experience in Risk Analytics or related data science roles, preferably within the BFSI sector.
• Bachelor’s or Master’s degree in Engineering, Economics, Statistics, Mathematics, or a related quantitative discipline; a preference for candidates with an engineering background.
• Proficiency in SQL for complex data querying and thorough data analysis.
• Strong programming skills in Python and/or R, with hands-on experience applying statistical algorithms and machine learning techniques in real-world business contexts.
• Experience in scorecard development, no-code low code ML development platforms, portfolio monitoring, or policy analytics is highly desirable.
• Prior experience mentoring junior team members is an advantage.

This role is for one of worko's clients, a leading E-commerce platform:

About the role

Are you a strategic thinker with a passion for solving large-scale problems using data? Do you enjoy mentoring high-performing teams and building ML systems that directly impact millions of users? We're looking for a Data Science Manager to lead a team of skilled data scientists in building intelligent systems that power our client's next phase of growth.

In this role, you’ll own the data science roadmap for a key business charter, guiding the team through ambiguity and complexity to deliver production-grade ML solutions. You’ll work closely with product, tech, and business leaders to translate complex challenges into scalable, measurable, and impactful outcomes. As a people and technical leader, you’ll ensure model efficiency, system reliability, and scientific excellence while fostering a culture of innovation, collaboration, and continuous improvement.

Key Responsibilities

• Lead, grow, and mentor a high-performing team of data scientists and ML engineers.
• Own all data science systems and models in your charter — from strategy to deployment and monitoring.
• Collaborate with senior product, engineering, and business leaders to define and prioritize impactful DS initiatives.
• Drive platformization, system architecture decisions, and ML lifecycle improvements across the charter.
• Ensure model scalability, performance, and cost efficiency, while upholding best practices in experimentation and statistical rigor.
• Guide the team in reading and implementing state-of-the-art research, and facilitate build vs. buy decisions.
• Lead RCA for critical production issues and improve system observability, documentation, and service uptime.

Requirements

• Master’s degree (PhD preferred) in Machine Learning, Statistics, Computer Science, or a related quantitative field.
• 8+ years of experience in Data Science or Analytics, with at least 2–3 years of people management experience.
• Proven track record of building and deploying ML models in production at scale.
• Experience managing teams of 4+ data scientists/engineers and delivering across cross-functional charters.
• Deep expertise in ML algorithms, experimental design, and performance monitoring.
• Strong coding skills (Python, SQL) and familiarity with Big Data technologies like Spark, Hive, or Redshift.
• Ability to translate business needs into technical solutions, prioritize roadmaps, and estimate effort accurately.
• Strong communication and stakeholder management skills with a bias for action and clarity in execution.

Mandatory Requirements

• Master’s degree in Machine Learning, Statistics, Computer Science, or related quantitative field
• 8+ years of experience in Data Science or Analytics
• 2–3 years of people management experience
• Proven track record of building and deploying ML models in production at scale
• Experience managing teams of 4+ data scientists/engineers
• Deep expertise in ML algorithms, experimental design, and performance monitoring
• Strong coding skills (Python, SQL)
• Familiarity with Big Data technologies like Spark, Hive, or Redshift
• Ability to translate business needs into technical solutions
• Strong communication and stakeholder management skills

Preferred Requirements

• Experience leading ML initiatives in B2C or e-commerce settings
• Contributions to internal tools, open-source libraries, or research publications
• Experience in personalization, recommendations, ranking, or supply chain ML problems
• Strong understanding of ML system performance trade-offs

Salary

100-120 lpa

This role is for one of worko's clients, a leading E-commerce platform:About the role Are you a strategic thinker with a passion for solving large-scale problems using data? Do you enjoy mentoring high-performing teams and building ML systems that directly impact millions of users? We're looking for a Data Science Manager to lead a team of skilled data scientists in building intelligent systems that power our client's next phase of growth. In this role, you’ll own the data science roadmap for a key business charter, guiding the team through ambiguity and complexity to deliver production-grade ML solutions. You’ll work closely with product, tech, and business leaders to translate complex challenges into scalable, measurable, and impactful outcomes. As a people and technical leader, you’ll ensure model efficiency, system reliability, and scientific excellence while fostering a culture of innovation, collaboration, and continuous improvement. Key ResponsibilitiesLead, grow, and mentor a high-performing team of data scientists and ML engineers.Own all data science systems and models in your charter — from strategy to deployment and monitoring.Collaborate with senior product, engineering, and business leaders to define and prioritize impactful DS initiatives.Drive platformization, system architecture decisions, and ML lifecycle improvements across the charter.Ensure model scalability, performance, and cost efficiency, while upholding best practices in experimentation and statistical rigor.Guide the team in reading and implementing state-of-the-art research, and facilitate build vs. buy decisions.Lead RCA for critical production issues and improve system observability, documentation, and service uptime.RequirementsMaster’s degree (Ph D preferred) in Machine Learning, Statistics, Computer Science, or a related quantitative field.8+ years of experience in Data Science or Analytics, with at least 2–3 years of people management experience.Proven track record of building and deploying ML models in production at scale.Experience managing teams of 4+ data scientists/engineers and delivering across cross-functional charters.Deep expertise in ML algorithms, experimental design, and performance monitoring.Strong coding skills (Python, SQL) and familiarity with Big Data technologies like Spark, Hive, or Redshift.Ability to translate business needs into technical solutions, prioritize roadmaps, and estimate effort accurately.Strong communication and stakeholder management skills with a bias for action and clarity in execution.Mandatory RequirementsMaster’s degree in Machine Learning, Statistics, Computer Science, or related quantitative field8+ years of experience in Data Science or Analytics2–3 years of people management experienceProven track record of building and deploying ML models in production at scaleExperience managing teams of 4+ data scientists/engineersDeep expertise in ML algorithms, experimental design, and performance monitoringStrong coding skills (Python, SQL)Familiarity with Big Data technologies like Spark, Hive, or RedshiftAbility to translate business needs into technical solutionsStrong communication and stakeholder management skillsPreferred RequirementsExperience leading ML initiatives in B2 C or e-commerce settingsContributions to internal tools, open-source libraries, or research publicationsExperience in personalization, recommendations, ranking, or supply chain ML problemsStrong understanding of ML system performance trade-offsSalary 100-120 lpa

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, our most valuable asset is our people. Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning; bold ideas; courage and passion to drive life-changing impact to ZS.

Our most valuable asset is our people .

At ZS we honor the visible and invisible elements of our identities, personal experiences and belief systems—the ones that comprise us as individuals, shape who we are and

make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about. 

About Advanced Data Science (ADS) : ZS’s Advanced Data Science group is focused on creating practical impact for clients across various industries such as Healthcare and Bio-Tech, Hi-Tech & Telecommunication, Financial Services and Travel through advanced analytics and emerging data sources. Emerging datasets include both unstructured datasets (for example, text, voice, image, etc.) and semi-structured datasets (for example, patientlevel records). Advanced analytical techniques span a range of innovative machine learning, artificial intelligence, advanced statistics and optimization approaches.

Being part of the ADS group at ZS will be an opportunity for you to work on cutting-edge solutions, utilizing new age data sources to shape innovations across multiple areas, for our clients and the broader ZS community.

A key enabler of our services is leveraging data in delivering client solutions. The data available about customers is getting richer and the problems that our customers are trying to answer continue to evolve. In our endeavor to stay ahead in providing solutions to these evolving complex problems, ZS has set up an Advanced Data Science which has three major focus areas:

Data Science Managers (DSMs) design, develop and execute analytic techniques on large, complex, structured and unstructured data sets (including big data) to help clients make better fact-based decisions. DSMs will develop new offerings/solutions, drive client impact by delivering client solutions and shape the ZS point of view in this space. You will be responsible for applying analytical techniques to model complex business problems, uncovering insights, and identifying opportunities using statistical, algorithmic, mining, and visualization techniques.

What You’ll Do:

What You’ll Bring:

Data Science + Gen AI with below mandatory skills.

Must to Have : Agent Framework, RAG Framework, Chunking Strategies, LLMs, AI on cloud

Services, Open Source Frameworks like Langchain, Llama Index, Vector Database, Token

Management, Knowledge Graph, Vision

Exp Range - 10 to 12 years

Requirements

Major Duties & Responsibilities

•  Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business

questions 

•  Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment

and operationalization of projects 

•  Influence machine learning strategy for Digital programs and projects

•  Make solution recommendations that appropriately balance speed to market and analytical soundness

•  Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor 

•  Develop analytical / modelling solutions using a variety of commercial and open-source tools (e.g., Python, R,

TensorFlow)

•  Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations.

•  Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations,

scenarios, and stories.

•  Create algorithms to extract information from large, multiparametric data sets.

•  Deploy algorithms to production to identify actionable insights from large databases.

•  Compare results from various methodologies and recommend optimal techniques. 

•  Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations,

scenarios, and stories.

•  Develop and embed automated processes for predictive model validation, deployment, and implementation 

•  Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science

•  Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate

reusability, and reliability upon deployment 

•  Lead discussions at peer review and use interpersonal skills to positively influence decision making

•  Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts; make

impactful contributions to internal discussions on emerging practices

•  Facilitate cross-geography sharing of new ideas, learnings, and best-practices

 Required Qualifications

•  Bachelor of Science or Bachelor of Engineering at a minimum.

•  10-12 years of work experience as a Data Scientist

•  A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to

quickly cycle hypothesis through the discovery phase of a project

•  Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL,

Hadoop/Hive, Scala)

•  Good hands-on skills in both feature engineering and hyperparameter optimization

•  Experience producing high-quality code, tests, documentation

•  Experience with Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Azure ML,

Synapse, Databricks

•  Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine

learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies

•  Proficiency in statistical concepts and ML algorithms

•  Good knowledge of Agile principles and process 

•  Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team

•  Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and

results

•  Self-motivated and a proactive problem solver who can work independently and in teams

Benefits

Work with one of the Big 4's in India

Position- Data Science Manager

Experience- 5-8 yr

Location-Chennai

Working Mode- Hybrid

Skills - 5yr hand on experience in Data Science, AI, Gen AI

Responsibilities :

• Implement the complete analytical section of the product based on the defined

functional scope, including necessary documentation and prototypes.

• Extract, collate, and cleanse data from various entities.

• Identify suitable databases (SQL/NoSQL) for data storage and various technology

stacks and libraries for data analysis and processing.

• Implement industry-standard statistical models with Machine Learning and Deep

Learning algorithms, incorporating predictive and auto-learning capabilities.

• Identify meaningful insights and foresights from data and metadata sources

based on the models.

• Interpret and communicate findings to the product manager to derive more

business strategies.

• Visualize various dimensions of data for both web and mobile platforms.

• Showcase output through demos, prototypes, and working systems in regular

review meetings.

• Continuously refine models for accuracy.

• Analyze, review, and track trends and tools in Data Sciences, Machine Learning,

Artificial Intelligence, and Augmented Intelligence, and appropriately apply these

learnings to the product.

• Interface the analytical system with transaction systems for both information

reporting and to process actionable items derived through analytics.

• Ensure Quality, Security, Performance, Scalability, Reliability, and Availability are

key factors in the implementation of the analytics system.

• Deploy and train various Large Language Models (LLMs) for AI agents and domain-

specific applications.

• Implement Retrieval Augmented Generation (RAG) pipelines along with Vector

databases to enhance the intelligence of LLMs and agent performance.

• Stay up-to-date with advancements in AI, including emerging LLM architectures

and agentic AI frameworks and technologies.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a

related quantitative field.

• 5-7 years of experience in data science, with a proven track record of leading and

implementing data science projects.

• Strong expertise in statistical modeling, machine learning, and deep learning

algorithms.

• Proficiency in programming languages such as Python or R.

• Experience with SQL/NoSQL databases and big data technologies.

• Familiarity with data visualization tools.

• Experience with LLMs, RAG pipelines, and vector databases is highly desirable.

• Excellent communication and interpersonal skills, with the ability to interpret and

present complex data insights to non-technical stakeholders.

• Ability to work independently and collaboratively in a fast-paced environment.

• Experience in the banking domain is an added advantage.

Position- Data Science Manager

Experience- 5-8 yr

Location-Chennai

Working Mode- Hybrid

Skills - 5yr hand on experience in Data Science, AI, Gen AI

Responsibilities :

• Implement the complete analytical section of the product based on the defined

functional scope, including necessary documentation and prototypes.

• Extract, collate, and cleanse data from various entities.

• Identify suitable databases (SQL/NoSQL) for data storage and various technology

stacks and libraries for data analysis and processing.

• Implement industry-standard statistical models with Machine Learning and Deep

Learning algorithms, incorporating predictive and auto-learning capabilities.

• Identify meaningful insights and foresights from data and metadata sources

based on the models.

• Interpret and communicate findings to the product manager to derive more

business strategies.

• Visualize various dimensions of data for both web and mobile platforms.

• Showcase output through demos, prototypes, and working systems in regular

review meetings.

• Continuously refine models for accuracy.

• Analyze, review, and track trends and tools in Data Sciences, Machine Learning,

Artificial Intelligence, and Augmented Intelligence, and appropriately apply these

learnings to the product.

• Interface the analytical system with transaction systems for both information

reporting and to process actionable items derived through analytics.

• Ensure Quality, Security, Performance, Scalability, Reliability, and Availability are

key factors in the implementation of the analytics system.

• Deploy and train various Large Language Models (LLMs) for AI agents and domain-

specific applications.

• Implement Retrieval Augmented Generation (RAG) pipelines along with Vector

databases to enhance the intelligence of LLMs and agent performance.

• Stay up-to-date with advancements in AI, including emerging LLM architectures

and agentic AI frameworks and technologies.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a

related quantitative field.

• 5-7 years of experience in data science, with a proven track record of leading and

implementing data science projects.

• Strong expertise in statistical modeling, machine learning, and deep learning

algorithms.

• Proficiency in programming languages such as Python or R.

• Experience with SQL/NoSQL databases and big data technologies.

• Familiarity with data visualization tools.

• Experience with LLMs, RAG pipelines, and vector databases is highly desirable.

• Excellent communication and interpersonal skills, with the ability to interpret and

present complex data insights to non-technical stakeholders.

• Ability to work independently and collaboratively in a fast-paced environment.

• Experience in the banking domain is an added advantage.