Tech Stack

Description

You will lead the design and optimization of incentive systems at Robinhood, building predictive and causal ML models to drive growth and retention. Your work will directly influence how millions of users engage with the platform.

Requirements

• 5+ years applying ML in production, in growth, incentives, marketplace, or personalization
• Proven track record owning models end-to-end
• Expertise in uplift modeling, causal inference, and experimentation design
• Strong skills in Python, SQL, and ML frameworks (scikit-learn, XGBoost, PyTorch or TensorFlow)
• Experience with Airflow and production pipelines

Responsibilities

• Build and deploy predictive and causal models for incentive targeting
• Design experiments to measure incremental impact and ROI of promotional programs
• Optimize incentive allocation algorithms under budget and policy constraints
• Monitor production systems and propose algorithmic improvements
• Influence long-term vision for growth modeling and personalization