Title and Summary

Senior Data Scientist

Overview:
We are seeking a Senior Data Scientist to design, develop, and deploy machine learning models that power Ad targeting, ranking, and bidding optimization in real-time or near real-time environments. This role will be instrumental in advancing Mastercard's commerce media and AdTech capabilities through data-driven personalization, measurement, and optimization solutions.

About the Role:
• Design, build, and deploy machine learning models for ad targeting, ranking, and bidding optimization.
• Develop and scale personalization and recommendation systems using large-scale transaction and behavioral datasets.
• Lead the design and implementation of incrementality testing frameworks, including lift measurement and causal inference methodologies, to evaluate campaign effectiveness.
• Build and enhance attribution models, including multi-touch and probabilistic attribution approaches across channels and devices.
• Partner closely with product, engineering, analytics, and business teams to translate business objectives into scalable data science solutions.
• Optimize machine learning models for accuracy, performance, latency, and scalability in production environments.
• Contribute to the architecture, design, and evolution of Mastercard's AdTech and commerce media products.
• Drive experimentation strategies, including A/B testing and advanced measurement frameworks.
• Stay current with emerging trends and technologies across the AdTech ecosystem, including DSPs, SSPs, RTB protocols, identity resolution, privacy-preserving techniques, and digital advertising measurement.

All About You
• Experience in Data Science, Machine Learning, AdTech (Preferred), Marketing Science, or a related field is required for this position.
• Proven experience building and optimizing ad bidding systems, including RTB optimization, budget pacing, bid shading, and auction-based decisioning.
• Hands-on expertise developing personalization, recommendation, and targeting systems at scale.
• Strong background in incrementality measurement, experimentation, A/B testing, causal inference, and advanced attribution modeling.
• Deep understanding of the digital advertising ecosystem, including DSPs, SSPs, ad exchanges, identity solutions, targeting strategies, and measurement methodologies.
• Proficiency in Python and related data science libraries, with strong experience in data manipulation, feature engineering, and model development.
• Experience working with large-scale distributed data processing frameworks such as Apache Spark.
• Demonstrated success deploying machine learning models into production environments, including batch and real-time pipelines, APIs, monitoring, and model lifecycle management.
• Strong foundation in statistics, machine learning algorithms, optimization techniques, and predictive modeling.
• Experience leveraging cloud platforms such as AWS, Azure, or GCP, along with modern ML infrastructure and MLOps tools.
• Excellent communication and stakeholder management skills, with the ability to explain complex analytical concepts to both technical and non-technical audiences.
• Ability to thrive in a fast-paced, highly collaborative environment and influence technical and business

This position is currently only available to local candidates in the San Francisco area. Relocation is not currently available for this position.

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.

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 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; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.

Pay Ranges
San Francisco, California: $138,000 - $221,000 USD