Sr. Data Scientist, Programmatic Algorithms

What you'll do

• Build and deploy pricing, yield, and inventory-allocation models, including real-time inference and adaptive feedback systems.
• Own programmatic data infrastructure, feature engineering, model monitoring, and the full model lifecycle.
• Run experiments to measure business impact and communicate findings and tradeoffs to stakeholders.

What they ask for

• 5+ years in data science, ML engineering, or quantitative research, including at least 2+ years building and 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.
• Production ML experience, including real-time inference, monitoring, retraining pipelines, and SLO ownership; experience building high-volume data pipelines, feature stores, and training infrastructure.
• Strong Python and SQL; ML libraries, large-scale data tools, real-time model deployment, and experience with causal inference and online experiment design.

Nice to have

• Direct SSP, DSP, or exchange-side yield optimization experience; auction theory knowledge.
• Experience with contextual bandits, 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 (amount not specified; contingent on Company performance); Restricted Stock Unit (RSU) grant (amount not specified).

Tools

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

AI focus

Develops machine-learning systems for programmatic auction pricing, yield optimization, inventory allocation, and real-time decisioning, including contextual bandits, reinforcement-learning signals, and online learning where appropriate.