Data Scientist

Mastercard•San Francisco, CA

3d•Remote

About The Position

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. Data Scientist Overview: Are you passionate about building scalable, high-performance data platforms that power personalized experiences for millions of users? Do you thrive in a fast-paced environment where innovation and collaboration drive success? Join the Loyalty group at Mastercard, where we connect anonymized transaction data with a robust advertising network to deliver highly personalized card-linked offers. We are looking for a Senior Data Scientist who brings deep technical expertise, a strong foundation in software engineering, and a passion for solving complex data challenges. You’ll work on mission-critical projects that shape the future of Mastercard’s offers platform, leveraging cutting-edge technologies in Data, cloud computing, and real-time processing. This is an exciting opportunity to work with a collaborative, agile team that values creativity, continuous learning, and delivering high-quality software at scale. About the Role: We are looking for a Data Scientist with a strong foundation in both data science and data engineering. This role requires someone who can not only build predictive models but also design, develop, and maintain scalable data pipelines and infrastructure. You will work cross-functionally to turn data into actionable insights and production-ready solutions.

Requirements

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related field
Multiple years of professional experience in data science and/or data engineering roles
Strong programming skills in SQL and Python is required
Hands-on experience with traditional machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
Experience building data pipelines using tools like Airflow and Spark
Solid understanding of statistics and probability

Nice To Haves

Machine Learning & Statistical Modeling
Data Engineering & Pipeline Development
SQL & Data Manipulation
Cloud & Big Data Technologies (Spark, Hadoop)
Problem-solving and critical thinking
Strong communication skills

Responsibilities

Develop, validate, and deploy machine learning models for business use cases
Perform exploratory data analysis (EDA) to uncover trends, patterns, and insights
Apply statistical techniques to solve complex business problems
Communicate findings clearly to stakeholders using visualizations and reports
Design and run A/B tests and experiments
Build and maintain scalable data pipelines (ETL/ELT)
Work with large datasets in distributed environments
Ensure data quality, integrity, and reliability across systems
Optimize data workflows and processing performance
Partner with product, engineering, and business teams to define data-driven solutions
Translate business requirements into technical implementations
Deploy models into production and monitor their performance
Contribute to best practices in documentation, and reproducibility

Benefits

insurance (including medical, prescription drug, dental, vision, disability, life insurance)
flexible spending account and health savings account
16 weeks of new parent leave
up to 20 days of bereavement leave
80 hours of Paid Sick and Safe Time
25 days of vacation time
5 personal days
10 annual paid U.S. observed holidays
401k with a best-in-class company match
deferred compensation for eligible roles
fitness reimbursement or on-site fitness facilities
eligibility for tuition reimbursement