Sr. Data Scientist, Programmatic Algorithms

What you'll do

• Develop and deploy pricing, yield, forecasting, and inventory-allocation models; measure their impact through experiments.
• Build data pipelines and features, and operate low-latency production inference, monitoring, and model lifecycle systems.
• Develop adaptive learning and feedback mechanisms, and communicate model tradeoffs and findings to cross-functional partners.

What they ask for

• 5+ years in data science, ML engineering, or quantitative research, including 2+ years deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain.
• Demonstrated understanding of programmatic auction mechanics and applying ML across the supply-demand stack.
• Experience independently taking models to production, designing high-volume data pipelines and feature infrastructure, and deploying low-latency inference.
• Strong Python and SQL; proficiency with ML libraries and large-scale data tools; experience with causal inference and online experiment design.

Nice to have

• Direct SSP, DSP, or exchange-side yield optimization experience; familiarity with auction theory.
• Experience with contextual bandits or reinforcement learning, online learning, privacy-preserving ML, or GCP/Databricks tools.

Pay

$165,000 - $185,000 USD per year base salary; additional 5% variable annual bonus contingent on Company performance; eligible to receive a Restricted Stock Unit (RSU) grant.

Tools

Python, SQL, scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow, Spark, Kafka

AI focus

Applies machine learning to programmatic auction pricing, yield optimization, inventory allocation, and real-time decisioning; includes contextual bandits, reinforcement-learning signals, and online learning where appropriate.