Quantitative Analyst

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The Opportunity

This is a rare opportunity to join an award-winning investment company led by two accomplished executives with more than 50+ years of combined experience. You will be working alongside a small team working across a variety of functions (handling portfolio management, research, software engineering, operations, and investor relations/sales), so regular internal interaction with all parts of the business is a necessity. Working across work streams allows us to be creative and combine cross-function ideas to generate better solutions. Collaboration across teams will allow you to gain exposure to the investment side of the fund, where regular discussions on trading opportunities and risk assessment are held.

The Role

You will work within the quant team to maintain and add to our tech stack in addition to undertaking new analysis to help with the firm’s investment objectives, reporting directly to our Head of Quant Research. Examples of projects/areas you would be exposed to:

• Design and backtest systematic trading signals through statistical modelling, portfolio simulation, in collaboration with the investment team to expand our multi-asset strategies
• Optimise our proprietary suite of trading algorithms and risk management tools, focusing on computational efficiency and statistical robustness
• Research and analyse alternative data sources to generate investment insights, develop statistical models to validate hypotheses, and deliver actionable findings to the investment team

Minimum Qualifications 

• 1-2 years of experience in a role requiring quantitative analysis and software development skills. Experience in financial markets, data science, or similar analytical fields is preferred
• Graduated with distinction in Computer Science,  Mathematics, Physics, or related fields (Bachelor's, Master's, PhD)
• Familiarity with common statistical concepts and the ability to undertake independent research/data analysis
• Strong programming principles with proven ability to write production-grade Python code, including testing and documentation
• Strong interpersonal skills with a keenness to work in a highly collaborative environment.
• Ambitious and confident, but humble

Preferred Qualifications 

• Personal experience or project focused on data within the digital asset  ecosystem or financial space
• Experience implementing machine learning models, with emphasis on statistical learning methods and feature engineering for time series data
• Demonstrated ability to research market inefficiencies through statistical arbitrage techniques and factor modelling across multiple asset classes