- Company Name
- FRANFINANCE
- Job Title
- Data Scientist
- Job Description
-
Job Title: Data Scientist – Risk Modelling
Role Summary
Develop, calibrate, and maintain quantitative risk models for a retail credit and services business. Analyze large datasets, create predictive models, validate results, and automate model lifecycle activities to support risk assessment, decision‑making, and regulatory compliance.
Expectations
- Minimum 4–5 years of experience in a bank, financial institution, regulator, credit‑rating agency, or consulting firm.
- Proven track record in risk modelling, statistics, and econometrics, with practical knowledge of Basel II/III regulatory requirements.
- Strong foundation in data science, machine learning, and data visualization applied to risk.
Key Responsibilities
- Design and analyze modelling datasets, ensuring data quality and suitability for risk analysis.
- Build, calibrate, back‑test, and validate statistical, econometric, and machine‑learning risk models.
- Document model methodology and support audit validation processes.
- Collaborate on the development of data‑science solutions for new risk‑management projects.
- Participate in application design and development for in‑house and B2B2C partners.
- Automate production pipelines for indicators, models, back‑tests, and reporting to feed risk dashboards.
Required Skills
- Expertise in risk‑modelling techniques: econometric models, statistical methods, probabilistic models, and machine‑learning algorithms.
- Proficiency in data‑visualisation and communication of complex findings.
- Knowledge of banking operations, products, and regulatory frameworks (Basile II/III).
- Strong programming skills – SAS (preferred), Python, and/or R.
- Excellent written and oral communication, with the ability to present technical concepts to non‑technical audiences.
- High reliability, analytical rigor, and organizational discipline.
- Curiosity, open‑mindedness, and an alert mindset for emerging risks.
Required Education & Certifications
- Bachelor’s or Master’s degree in Statistics, Mathematics, Econometrics, Actuarial Science, or a related quantitative field.
- Advanced coursework or certification in risk modelling, regulatory compliance, or data science is an advantage.