onsite
Lead Data Scientist - Credit Modelling & Data Products - Proactive Appointments
Data Scientist
Lead the design, development, and governance of credit risk models and data products, leveraging large‑scale financial datasets, advanced machine learning, and cloud‑based analytics to deliver predictive insights and business value.
About the role
Key Responsibilities
- Architect, develop, and maintain credit risk and propensity models using Python, statistical techniques, and machine learning algorithms.
- Transform massive financial datasets into scalable data pipelines and feature stores on AWS (S3, Redshift, SageMaker).
- Collaborate with product, engineering, and business teams to define data product requirements and translate them into analytical solutions.
- Establish model governance frameworks, including validation, monitoring, and documentation to ensure regulatory compliance.
- Mentor junior data scientists and promote best practices in code quality, reproducibility, and experiment tracking.
Requirements
- 5+ years of experience building production‑grade predictive models in finance or related domains.
- Strong proficiency in Python, SQL, and data‑visualization tools (e.g., Tableau, Power BI, or Plotly).
- Hands‑on experience with AWS services for data storage, processing, and model deployment.
- Deep understanding of statistical modeling, machine learning, and credit risk concepts.
- Proven ability to communicate complex analytical results to non‑technical stakeholders.
Skills
pythonmachine learningsqlaws