Lead Data Scientist, Credit Risk for SME Lending Portfolio

GoTyme ZA (South Africa); Cape Town; On-site; ZAR 600,000 - 1,300,000; Full time

Job summary

GoTyme ZA (South Africa) seeks a Data Scientist to own the end-to-end credit risk management for the FNB MCA portfolio, including strategy, modelling, and governance. You will partner with Risk, Data Science, and business stakeholders to drive measurable impact.

Requirements include 3–5 years in credit risk or data science within financial services, strong SQL and Python skills, and familiarity with IFRS 9. You will operate in a focused, autonomous role with cross-functional collaboration.

Qualifications

• Degree in mathematics, statistics, data science, or related quantitative field.
• 3–5 years of credit risk analysis or data science experience in banking, lending, fintech, or financial services, including independent delivery of credit risk work.
• Strong understanding of credit risk strategies, scorecards, models, and ML techniques for credit decisioning.
• Familiarity with IFRS 9 principles and their application to credit risk management, including ECL calculations.
• Strong analytical skills with the ability to interpret complex financial and trade data and make informed decisions.
• Proficiency in SQL and Python; Databricks experience is advantageous.
• Excellent communication and presentation skills for non-technical stakeholders.
• Ability to work independently, structure ambiguous problems, take ownership, and manage multiple priorities.

Responsibilities

• Own end-to-end credit risk management of the FNB MCA portfolio, driving the work plan with Risk and Data Science teams.
• Monitor portfolio performance, identify trends and risks, and recommend mitigation or growth actions.
• Set and manage the portfolio’s credit risk strategy, policy, and decisioning rules within risk appetite.
• Develop, maintain, implement, and monitor scorecards and credit risk models across the lifecycle.
• Ensure models are developed, reviewed, documented, and governed per model risk standards.
• Support model validation with clear documentation, data definitions, assumptions, and results.
• Collaborate with data engineering to deploy models and decisioning logic to production.
• Prepare and present reports to senior management with key risk metrics and recommendations.
• Develop stress testing scenarios and conduct sensitivity analyses for portfolio resilience.
• Monitor regulatory changes, especially IFRS 9, and ensure compliant reporting.

Skills

SQL

Python

Credit risk

Modeling

IFRS9

Education

Quantitative degree

Tools

Databricks

Job description

GoTyme ZA (South Africa) seeks a Data Scientist to own the end-to-end credit risk management for the FNB MCA portfolio, including strategy, modelling, and governance. You will partner with Risk, Data Science, and business stakeholders to drive measurable impact.

Requirements include 3–5 years in credit risk or data science within financial services, strong SQL and Python skills, and familiarity with IFRS 9. You will operate in a focused, autonomous role with cross-functional collaboration.