Data Scientist – Investment & Short Term Insurance – Johannesburg – R550k to R750k per annum

E-Merge; Johannesburg; On-site; ZAR 600,000 - 900,000; Full time

Job summary

A leading financial services company is seeking a Data Scientist to transform complex datasets into actionable insights. In this hybrid role, you will design predictive models and build scalable data pipelines while mentoring junior analysts. The ideal candidate will have a strong background in data science, particularly within finance, and a proven ability to deploy models in production environments. This position offers a competitive salary package, negotiable based on experience.

Qualifications

• 5-7 years hands-on data science experience, preferably in finance.
• Strong expertise in ML libraries (Scikit-learn, XGBoost, TensorFlow/PyTorch).
• Proven track record deploying models to production.

Responsibilities

• Design ML/quant models for manager selection and risk attribution.
• Build scalable data pipelines using Python, SQL, and Spark.
• Deliver real-time dashboards and APIs for risk exposure.

Skills

Python

SQL

Machine Learning

Data Analysis

Education

Bachelor's or Master's in Data Science, Stats, Comp Sci, Math, or Financial Engineering

Tools

Azure

AWS

Databricks

Snowflake

Spark

Job description

Join a financial services company as a Data Scientist transforming vast financial and short-term insurance datasets into actionable insights for portfolio managers, analysts, and risk teams.

You'll build predictive models, automate due-diligence workflows, and surface performance drivers spanning traditional market data and insurer-specific metrics such as claims frequency, loss ratios, and solvency capital requirements.

Responsibilities:

1. Design ML / quant models for manager selection, risk attribution, alpha forecasting, and factor analysis incorporating short-term insurance KPIs (e.g., combined ratio, reserve adequacy).
2. Build scalable pipelines (Python, SQL, Spark / Dask) that ingest, cleanse, and enrich multi-manager and insurance data.
3. Codify due-diligence, performance-benchmarking, and insurer-health monitoring into reproducible frameworks.
4. Deliver real-time dashboards and APIs highlighting manager alpha and insurance-portfolio risk exposure.
5. Partner with PMs, analysts, risk, and actuarial teams to translate business problems into data-driven solutions.
6. Mentor junior analysts; promote best practices in ML-Ops and model governance.
7. Stay current on AI / ML trends across investments and InsurTech; pilot relevant techniques (e.g., telematics-driven claims prediction, catastrophe risk modeling).
8. Contribute to our cloud-first stack (Azure / AWS, Databricks, Snowflake).

Qualifications and Experience:

1. Bachelor's or Master's in Data Science, Stats, Comp Sci, Math, or Financial Engineering.
2. 5-7 years hands-on data science experience (finance preferred).
3. Strong Python & SQL; expertise in ML libraries (Scikit-learn, XGBoost, TensorFlow / PyTorch).
4. Proven track record deploying models to production (CI / CD, monitoring, retraining).
5. Cloud & big data know-how (Azure / AWS, Spark, Databricks, Snowflake).

The reference number for this position is NG. It is a permanent hybrid role offering a salary up to Rk per annum, negotiable based on experience.