2 months ago
Responsibilities
- Design, build, and validate credit risk models using proprietary and external data.
- Develop data pipelines and feature logic for model training.
- Deploy models into production systems and monitor their performance.
- Collaborate with cross-functional teams to align modeling decisions with business needs.
- Define hiring standards and interview processes for future data science and ML roles.
Requirements
- 5+ years of experience in building models for production use cases.
- Strong command of supervised learning on tabular data.
- Proficient in data engineering, including ETL and feature pipelines.
- Expertise in Python and modern ML tools like pandas, scikit-learn, and TensorFlow.
- Solid statistical reasoning and ability to evaluate model performance.
- Proven track record of owning models from problem statement to production.
- Excellent communication skills to explain complex models to non-technical audiences.
- Team player with a commitment to fostering a supportive work environment.