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.

Qualifications

• 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 outcomes.

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

Pay

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