Senior Data Scientist-1 Job Listing at Mastercard in Pune, MH (Job ID R-272041)

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

Senior Data Scientist-1 Overview
The Issuer Fraud Solutions Data & Analytics team is seeking a Senior Data Scientist (L7) to join the Product Development organization within Services. This role is designed for a senior individual contributor who brings deep data science expertise combined with strong data engineering and automation skills to deliver scalable, production grade solutions.
In this role, you will work on large scale data processing, ETL pipelines, and advanced analytics, leveraging Python, Spark, and big data platforms. As an L7, you will operate as a technical leader—owning complex problem spaces, influencing architectural decisions, and raising engineering and data science standards across teams.

Role
As a Senior Data Scientist at Mastercard, you will:
• Lead the design, development, and optimization of large scale data pipelines and ETL processes supporting Mastercard products and analytics
• Build and maintain distributed data processing solutions using Python and Spark (PySpark) in high volume environments
• Work with big data platforms to ingest, transform, and curate data for analytics, modeling, and downstream consumption
• Drive automation of data workflows and operational processes to reduce manual effort and improve reliability
• Partner closely with data scientists, engineers, and product teams to translate business and product needs into scalable technical solutions
• Ensure end to end data quality, performance, resiliency, and observability across production pipelines
• Optimize Spark workloads for performance, scalability, and cost efficiency
• Provide technical leadership through design reviews, best practices, and architectural guidance
• Support production systems through monitoring, troubleshooting, and continuous improvement

All About You
Required Experience & Skills
• Extensive hands on experience using Python for data processing, automation, and analytics
• Strong expertise with Apache Spark / PySpark in distributed, large scale environments
• Proven experience working with big data systems involving large volumes, complex schemas, or high throughput processing
• Deep understanding of ETL design, including data ingestion, transformation, validation, and optimization
• Demonstrated ability to build automated, repeatable data pipelines and workflows
• Strong knowledge of distributed data processing concepts and performance tuning
• Ability to independently own complex technical domains and deliver production ready solutions
Preferred Qualifications
• Experience with Ozone or similar internal or enterprise data platforms
• Background working in regulated, high availability, or mission critical environments
• Familiarity with data quality frameworks, monitoring, and alerting
• Experience collaborating across geographically distributed teams
• Prior experience influencing technical strategy beyond immediate project scope

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.

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