Senior Data Scientist, Programmatic Algorithms

Responsibilities

• Design and deploy ML models to optimize auction pricing, bid shading, and yield
• Build real-time pricing algorithms and inventory allocation logic
• Design and own data infrastructure including event pipelines and feature stores
• Deploy models to production real-time inference environments and manage latency/reliability
• Execute A/B and holdout experiments to measure causal impact on yield and revenue
• Research and implement adaptive systems like contextual bandits and reinforcement learning
• Collaborate with Product and Engineering teams to translate business needs into technical solutions

Requirements

• 5+ years in data science, ML engineering, or quantitative research
• 2+ years building/deploying ML models in programmatic advertising or ad tech
• Deep understanding of programmatic auction mechanics (RTB, header bidding, floor pricing)
• Proficiency in Python and SQL
• Experience with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow)
• Experience with large-scale data tools (Spark, Kafka)
• Strong grasp of causal inference and experiment design
• Bachelor's degree in a quantitative field (CS, Statistics, Math, etc.); Master's/PhD preferred

Preferred Qualifications

• Direct experience with SSP, DSP, or exchange-side yield optimization
• Familiarity with auction theory and revenue equivalence
• Experience with reinforcement learning or multi-armed bandits
• Knowledge of privacy-preserving ML (differential privacy, federated learning)
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub)

Benefits

• Extended health, vision, and dental coverage
• Flexible PTO policy
• Mental health support and gym reimbursement
• Restricted Stock Units (RSUs)
• Paid parental leave (26 weeks primary, 13 weeks secondary)
• Technology and internet stipends