Risk Data Scientist

BigTalent; Wes-Kaap; Hybrid; ZAR 600 000 - 800 000; Full time

Job summary

A leading analytics firm in South Africa is seeking a skilled data scientist to join their high-impact analytics team. This role involves building and refining quantitative models for SME lending, developing machine learning models, and delivering analytical solutions. The ideal candidate will possess a relevant degree and have over 4 years of experience in data science, with strong skills in Python, SQL, and data visualization tools. This position operates in a hybrid work environment, primarily based in Cape Town.

Qualifications

• 4+ years of experience in data science, with expertise in predictive modeling and machine learning.
• Strong business acumen and ability to work independently or within a team.
• Excellent communication and problem-solving skills.

Responsibilities

• Build and refine quantitative models to support SME lending decisions.
• Develop and evaluate machine learning models and translate findings into actionable recommendations.
• Pull, clean, and prepare data independently using SQL and/or Python.

Skills

Predictive modeling

Machine learning expertise

Python proficiency

SQL (BigQuery)

Data visualization tools (Tableau, Looker Studio)

Analytical skills

Problem-solving skills

Excellent communication

Education

Bachelors or Masters degree in Statistics, Mathematics, Computer Science, Engineering or related field

Tools

Python

R

SQL

BigQuery

Tableau

Looker Studio

GCP

Hadoop

Spark

Job description

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).

Role details:

• 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.