Risk Data Scientist, Cape Town

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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