Data Scientist

AiR; Cape Town; Hybrid; ZAR 600,000 - 900,000; Full time

Job summary

A leading investment management firm based in Cape Town is seeking an experienced Data Scientist to enhance investment decision-making through innovative data science strategies. The ideal candidate will have a strong programming background in Python and a deep understanding of machine learning and statistical modeling. This hybrid position involves evaluating alternative datasets and developing machine learning models for financial markets, making it vital for the future of systematic investing.

Qualifications

• 13 years in a data science or quantitative research role, preferably in finance or recently qualified Masters/PhD.
• Proven track record of delivering production-ready data science solutions.

Responsibilities

• Design and implement data science strategies to enhance investment decisions.
• Identify and evaluate alternative data sources for predictive insights.
• Develop bespoke machine learning algorithms for financial use cases.
• Build, test, and deploy end-to-end data and model pipelines.
• Collaborate closely with portfolio managers and engineers.
• Contribute to internal libraries and infrastructure.

Skills

Strong programming experience in Python

Machine learning

Statistical modelling

Time series analysis

Education

Honours, Masters and/or PhD in a quantitative field

Tools

Cloud environments (Azure, AWS, GCP)

Distributed computing frameworks

Job description

Overview

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. You'll 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.