Data Scientist
Reporting line : Head of Data Science
Location : Cape Town (Southern Suburbs)
Business Unit : Investment Management
As a Data Scientist, you'll be instrumental in shaping the future of systematic investing. This is a hybrid research-engineering position that blends rigorous quantitative research with practical implementation. Youll work on sourcing and evaluating alternative datasets, developing bespoke machine learning models for financial markets, and building scalable, production-grade pipelines that power real-time investment signals.
Duties & Responsibilities
- Design and implement data science strategies that enhance investment decision-making.
- Identify, acquire, and evaluate alternative data sources that may provide predictive insights into financial markets.
- Develop bespoke machine learning algorithms tailored to financial use cases (e.g. risk forecasting, sentiment analysis, market regime detection).
- Build, test, and deploy end-to-end data and model pipelines that operate reliably at scale.
- Collaborate closely with portfolio managers, quantitative analysts, and software engineers.
- Contribute to internal libraries, tooling, and infrastructure to streamline data science workflows.
- Stay current with academic and industry research, applying innovative techniques where relevant.
Required Experience
13 years in a data science or quantitative research role, preferably in finance or another high-impact research domain, OR a recently qualified Masters or PhD graduate.Proven track record of delivering production-ready data science solutions.
Required Qualifications
Honours, Masters and / or PhD in a quantitative field (Computer Science, Statistics, Engineering, Applied Mathematics, Quantitative Finance or similar).Financial certification advantageous but not required.
Key Competencies
Strong programming experience in Python with good software engineering practices (modular code, testing, version control, etc.).Solid understanding of machine learning, statistical modelling, and time series analysis.Experience with cloud environments (Azure, AWS, or GCP) and distributed computing frameworks is a plus.Familiarity with data infrastructure (databases, ETL pipelines, containerisation, orchestration tools) is highly desirable.Experience using LLMs and working with unstructured / alternative data (text, news, satellite, geolocation) is a bonus.