Risk Data Scientist

You’ll join a high-impact analytics team supporting an SME lending (Merchant Cash Advance) business, where your work directly influences credit decisioning and portfolio performance.

This is a hands‑on role for a true data scientist—someone who can pull, prep, and analyse their own data, build robust models (beyond reporting), and partner closely with the business in a fast‑moving, lean environment. The team is primarily Cape Town‑based and typically works in a hybrid setup (around 2–3 days in office). • Build and refine quantitative models to support SME lending decisions, including credit risk and cash flow modelling approaches. • Develop and evaluate machine learning models (e.g., tree‑based/boosted models) and translate findings into clear, actionable recommendations. • Pull, clean, and prepare data independently using SQL and/or Python, ensuring analysis is reproducible and fit for purpose. • Partner closely with business stakeholders (e.g., credit, operations, collections) to understand problems, define success metrics, and deliver analytical solutions. • Support model handover to engineering for production deployment by documenting assumptions, features, and performance considerations. • Own and drive analytical workstreams end‑to‑end, operating effectively in a fast‑moving, lean team environment. Qualifications and Skills Requirements • Bachelors or Masters degree in Statistics, Mathematics, Computer Science, Engineering, or a related field. • 4+ years of experience in data science, with expertise in predictive modeling and machine learning. • Strong proficiency in Python or R, SQL (BigQuery), and data visualization tools (Tableau, Looker Studio). • Experience with machine learning algorithms and big data technologies (GCP, Hadoop, Spark). • Excellent communication, problem‑solving, and analytical skills. • Strong business acumen and ability to work independently or within a team.

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