Lead Data Scientist (AI/ML, Python, Langchain, GenAI, Pyspark, SQL)

India: Mastercard Technology Private Limited; Pune District; On-site; INR 5,500,000 - 9,000,000; Full time

Job summary

Mastercard is seeking a Lead Data Scientist (AI/ML, Python, LangChain, GenAI, PySpark, SQL) to join the Business & Market Insights team. You will work with product, client services and delivery, data & engineering to build differentiated analytics-driven products using GenAI and large-scale data.

You will design and deploy ML models, optimize pipelines and mentor junior data scientists, contributing to strategic initiatives across the organization.

Qualifications

• 8–12 years of experience in Data Science for products.
• Design, develop, and productionize ML/data science solutions for BMI.
• Develop traditional ML solutions including feature engineering, model training, validation, and deployment.
• Perform exploratory data analysis and translate datasets into insights.
• Build Generative AI applications using Python and GenAI frameworks, especially LangChain and LangGraph.
• Optimize data pipelines and ML/GenAI workflows for performance and scalability.
• Evaluate GenAI solutions for answer quality, groundedness, reliability, latency and cost.
• Write robust Python components following software engineering practices.
• Use PySpark to process and analyze large datasets in distributed environments.
• Write advanced, optimized SQL for data extraction and analytics.
• Collaborate with product managers, AI engineers, software engineers, and data scientists.
• Apply data privacy, security, responsible AI, monitoring and explainability controls.
• Conduct code reviews and mentor junior data scientists.

Responsibilities

• Drive the evolution of BMI products with a data science and engineering focus.
• Participate in exploration and development of data science for product development.
• Identify and evaluate AI/ML techniques and tools for models and analytics.
• Innovate with new data science approaches to solve business problems and generate insights.
• Partner with product, engineering and sales to prioritize data science problems.
• Evaluate trade-offs between analytics solutions considering performance and feasibility.
• Break large solutions into milestones to collect data and feedback.
• Champion releases to users and incorporate feedback.
• Work with cross-functional teams to define vision and culture.

Skills

Python

LangChain

GenAI

PySpark

SQL

ML Pipelines

Data Visualization

Mentoring

Tools

LangGraph

Job description

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Lead Data Scientist (AI/ML, Python, Langchain, GenAI, Pyspark, SQL) Lead, Data Scientist • Our Purpose The Business & Market Insights (B&MI) team within Mastercard's Services division creates products that help customers including financial institutions and merchants understand their customers and the market better. The B&MI Data Science team uses data from Mastercard transactions and other sources to build models and solutions that are needed for these products, at a globally scalable level across the different customer lifecycle stages. This role is for a Data Scientist that will work across Product, Client Services & Delivery, Data & Engineering and the broader teams, to deliver truly differentiated products driven by analytics & AI, leveraging rich data resources, AI platform capabilities and near real-time execution. We are developing multiple new products and capabilities using analytics & AI, and this role is central in that vision, from concept, technical design to market release and optimization. This role is positioned to drive new ideas forward by combining creative thought leadership with innovation and industry best practices. By entering in the early phase of a truly transformative and impactful strategic initiative, the experience is certain to be rewarding.

Requirements

• 8-12 years of overall career experience in Data Science function supporting Products
• Design, develop, and productionize machine learning and data science solutions that solve complex business problems within BMI.
• Develop traditional ML solutions covering feature engineering, model training, validation, evaluation, and deployment.
• Perform exploratory data analysis and translate complex datasets into actionable insights.
• Build Generative AI applications using Python and modern GenAI frameworks, particularly LangChain and LangGraph.
• Optimize data pipelines and ML/GenAI workflows for performance, scalability, maintainability, and reliability.
• Evaluate GenAI solutions for answer quality, groundedness, reliability, latency, and cost, rather than relying solely on prototype-level demonstrations.
• Develop robust and reusable Python components following sound software-engineering practices.
• Use PySpark to process, transform, and analyze large datasets efficiently in distributed environments.
• Write advanced, optimized SQL for data extraction, transformation, feature development, and analytical workloads.
• Collaborate with product managers, AI engineers, software engineers, and other data scientists to translate business requirements into technical solutions.
• Apply appropriate controls for data privacy, security, responsible AI, monitoring, and explainability.
• Conduct code reviews, establish reusable technical patterns, and mentor less-experienced data scientists.

Primary Responsibilities

• Drive the evolution of B&MI products with an impact focused on data science and engineering
• Participate in the exploration, application and development of data science for product development
• Participate in identification and evaluation of AI/ML techniques and tools to deliver models and analytics for product development
• Continuously innovate and determine new data science approaches & technologies to solve business problems and generate business insights & recommendations
• Partner with roles across the organization including product, engineering, and sales to determine the highest priority data science problems to solve in a customer-centric framework
• Evaluate trade-offs between many possible analytics solutions to a problem, taking into account performance, usability, technical feasibility, timelines, and differing stakeholder opinions to make a decision
• Break large solutions into smaller, releasable milestones to collect data and feedback from product managers, clients and other stakeholders
• Evangelize releases to users, incorporating feedback, and tracking usage to inform future development
• Work with small, cross-functional teams to define vision, establish team culture and processes
• Consistently focus on key drivers of organization value and prioritize operational activities accordingly
• Identify and act upon product improvement opportunities
• Provide technical leadership of junior colleagues as a senior member of the data science team, through technical and non-technical mentoring

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.