Senior Data Scientist, AdTech & Personalization

Mastercard; San Francisco (CA); On-site; USD 138,000 - 221,000; Full time

Job summary

Mastercard seeks a Senior Data Scientist to design, develop, and deploy ML models powering ad targeting, ranking, and bidding optimization in real-time or near real-time environments.

You will scale personalization using large transaction and behavioral datasets, lead incrementality testing, and collaborate with cross‑functional teams to translate business goals into scalable data science solutions. The role emphasizes production-ready models and advanced measurement frameworks.

Qualifications

• Experience in Data Science, Machine Learning, AdTech (preferred).
• Proven experience building ad bidding systems including RTB optimization.
• Hands-on expertise developing personalization and targeting systems at scale.
• Strong background in incrementality measurement, experimentation, A/B testing, causal inference, attribution modeling.

Responsibilities

• Design, build, and deploy ML models for ad targeting, ranking, and bidding optimization.
• Develop and scale personalization and recommendation systems.
• Lead incrementality testing frameworks including lift measurement and causal inference.
• Build and enhance attribution models across channels and devices.
• Collaborate with product, engineering, analytics, and business teams to translate objectives into scalable DS solutions.
• Optimize models for accuracy, latency, and scalability in production.
• Contribute to architecture and evolution of AdTech products.
• Drive experimentation strategies including A/B testing and advanced measurement.

Skills

Python

Apache Spark

ML modeling

A/B testing

Causal inference

Attribution modeling

RTB optimization

Data pipelines

Tools

AWS

Azure

GCP

ML tooling

Job description

Mastercard seeks a Senior Data Scientist to design, develop, and deploy ML models powering ad targeting, ranking, and bidding optimization in real-time or near real-time environments.

You will scale personalization using large transaction and behavioral datasets, lead incrementality testing, and collaborate with cross‑functional teams to translate business goals into scalable data science solutions. The role emphasizes production-ready models and advanced measurement frameworks.