Sr. Data Scientist, Programmatic Algorithms

What you'll do

• Design and deploy pricing, yield, and inventory-allocation models, including real-time auction decisions.
• Build the data pipelines, features, inference systems, and monitoring for production ML; manage the full model lifecycle.
• Run experiments to measure business impact and develop adaptive learning and feedback systems.

What they ask for

• 5+ years in data science, ML engineering, or quantitative research, including 2+ years building and deploying ML in programmatic advertising, ad tech, marketplace optimization, or a closely related domain.
• Demonstrated knowledge of programmatic auction mechanics and applying ML to supply-demand optimization.
• Production ML and data-infrastructure experience, including real-time inference, monitoring, retraining, feature stores, and high-volume, low-latency systems.
• Strong Python and SQL; experience with ML libraries, large-scale data tools, real-time model serving, and online causal experimentation.

Nice to have

• Master’s/PhD; SSP, DSP, or exchange-side yield optimization experience; auction theory or bandit/reinforcement-learning experience.
• Experience with GCP or Databricks/Spark; privacy-preserving ML, online learning, forecasting, or inventory management.

Pay

$165,000 - $185,000 USD per year base salary; 5% variable annual bonus contingent on Company performance (amount not specified); Restricted Stock Unit (RSU) grant (amount not specified)

Tools

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

AI focus

Build and deploy production ML for programmatic auction pricing, yield, inventory allocation, forecasting, and real-time decisioning; develop adaptive systems using contextual bandits, reinforcement-learning signals, and online learning where appropriate.