onsite
Staff Data Scientist, Machine Learning Credit Risk - Robinhood
Data Scientist
Lead the design and deployment of advanced machine‑learning models to assess and mitigate credit risk for a high‑growth fintech credit‑card portfolio, driving data‑driven decision making across the organization.
About the role
Key Responsibilities
- Architect, develop, and productionize machine‑learning models that predict credit risk, default probability, and customer behavior.
- Collaborate with product, engineering, and risk teams to translate business requirements into scalable data pipelines and analytical solutions.
- Lead experimentation, A/B testing, and model validation to ensure robustness, fairness, and regulatory compliance.
- Mentor junior data scientists and foster best practices in code quality, reproducibility, and model monitoring.
- Stay abreast of cutting‑edge research and integrate novel techniques (e.g., deep learning, causal inference) to maintain a competitive edge.
Requirements
- 5+ years of experience building and deploying production ML models, preferably in credit risk or financial services.
- Strong proficiency in Python and its data‑science ecosystem (pandas, scikit‑learn, PyTorch/TensorFlow).
- Expertise in statistical modeling, feature engineering, and evaluation metrics for credit risk.
- Hands‑on experience with SQL and cloud platforms such as AWS (SageMaker, EMR, Redshift).
- Demonstrated ability to communicate complex analytical insights to both technical and non‑technical stakeholders.
Skills
pythonmachine learningsqlaws