**Note – This vacancy is ideally earmarked for suitably qualified and experienced Employment Equity candidates. **Non-EE female candidates would also be considered.
Senior and strategic opportunity for a top-calibre Financial Engineer / Investment Quant with a successful investment track record and love for numbers, investments and information technology to join a leading investment team as 2IC.
Be responsible for researching, developing and enhancing the team’s investment research scope and processes, as well as infrastructure with the aim of improving long-term Alpha and be at the forefront of industry best practice.
• Consistently assess and advance the team’s research program, investment processes and research infrastructure;
• Drive the development of repeatable processes, models and algorithms;
• Drive progressive “AI” and “ML” adoption and implementation;
• Ensure data best practice, and play a critical role in building a data-driven culture and drive adoption, data knowledge and fluency;
• Develop frameworks to evaluate and manage Alpha research to continuously extract and enhance Alpha generation from current product offerings;
• Driving the research scope and pipeline:
• Drive technology discussions and analyze the gaps and best solutions;
• Collaborate with other teams and stakeholders;
• Responsible for broad data science and technology adoption, implementation, and standardization across investment infrastructure.
• Verifiable track record with 15 or more years’ experience in a comparable role, or in another quantitative finance field, having coded predictive models, across asset classes, in various scripting languages;
• Extensive experience as a senior investment research analyst / head of research;
• Relevant numerically-orientated Master’s degree;
• FAIS Compliant;
• Deep understanding of quantitative techniques, portfolio optimisation, risk & cost management with an affinity for, “AI” & “ML”, and its application in investment decision making;
• Experience in the assimilation of large amounts of quantitative and qualitative financial data, signal generation, testing, model validation, trade execution and cash management methodologies, portfolio construction, and rebalancing techniques, as well as risk management, reporting and visualization – all from first principles;
• Strong programming skills in Python and SQL, R is required;
• Functional background in version control, Github with LFS, TortoiseGit & CLI.