Senior Data Scientist (AI, ML, Pyspark, SQL)

This role requires the successful candidate to have the following: - 5-9 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. - Optimize data pipelines and ML workflows for performance, scalability, maintainability, and reliability. - 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. - Apply appropriate controls for data privacy, security, responsible AI, monitoring, and explainability. Good to have: - Understanding of building Generative AI applications using Python and modern GenAI frameworks.

- 5-9 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. - Optimize data pipelines and ML workflows for performance, scalability, maintainability, and reliability. - 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. - Apply appropriate controls for data privacy, security, responsible AI, monitoring, and explainability. Good to have: - Understanding of building Generative AI applications using Python and modern GenAI frameworks. The successful candidate’s primary responsibilities will be to: - Drive the evolution of Business & Market Insights products by applying Data Science and Artificial Intelligence to create models, tools and capabilities - 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

Title and Summary Senior Data Scientist (AI, ML, Pyspark, SQL) Overview 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.