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

Overview

Lead the design, build and productionization of machine learning and GenAI solutions for the Business & Market Insights (B&MI) team within Mastercard's Services division, from concept through market release and optimization.

What you'll do

• 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.
• Drive the evolution of B&MI products with an impact focused on data science and engineering.
• Identify and evaluate AI/ML techniques and tools to deliver models and analytics for product development.
• Partner with product, engineering, and sales to determine the highest priority data science problems to solve in a customer-centric framework.
• Evaluate trade-offs between analytics solutions considering performance, usability, technical feasibility, timelines, and differing stakeholder opinions.
• Break large solutions into smaller, releasable milestones and gather feedback from product managers, clients and other stakeholders.
• Provide technical leadership of junior colleagues as a senior member of the data science team, through technical and non-technical mentoring.

What you'll need

• 8-12 years of overall career experience in a Data Science function supporting products.

Details

• Location: Pune, India.
• Corporate security responsibility: abide by Mastercard's security policies, ensure confidentiality and integrity of information accessed, report suspected information security violations, and complete mandatory security trainings.