Lead Quant Mentor

About the Role

We are building a quantitative research graduate programme and are looking for an experienced quant professional to lead it end-to-end — from curriculum design and candidate selection through to mentorship, performance evaluation, and integration of graduates into live trading and research teams.

This role sits at the intersection of quantitative research, education, and talent strategy. You will own the full lifecycle of our Quant Bootcamp and ensure the pipeline consistently delivers researchers who can contribute to real alpha generation.

Graduates who complete the programme are integrated directly into our live trading pipeline — working on real capital, real markets, real constraints. This is not a training programme with a certificate at the end.

What You'll Own

• Curriculum & programme design — build and evolve a 3–6 month programme covering mathematics, statistics, ML, market microstructure, backtesting, risk management, and production pipelines; define milestone frameworks, stage-gate criteria, and hands-on projects grounded in real market data.
• Recruiting & assessment — define the candidate profile, design rigorous take-home assignments and research case studies, build a sourcing pipeline with TA and HR (universities, olympiads, Kaggle, open-source), and lead final-round interviews.
• Mentorship & development — provide direct mentorship, run research and code review sessions, and train participants on production infrastructure, data leakage prevention, and the realities of live-market research.
• Talent evaluation & business integration — assess performance throughout the programme, make clear decisions on progression or exits, and match graduates to open roles based on demonstrated strengths and team needs; own the handoff so graduates land well and contribute quickly. Integration means the graduate is operational in the trading pipeline within 30 days — not "onboarded", but contributing.
• Programme scalability — document processes, develop internal mentors, manage budget, and contribute to employer branding in the quant community.

What We're Looking For

Must-have:

• Hands-on background in quantitative research or quantitative trading in a professional setting.
• Deep familiarity with the full quant research stack: statistical modelling, ML, backtesting, and production pipelines.
• Strong mathematical foundations — probability, statistics, linear algebra, stochastic processes.
• Proven ability to assess and filter quant talent under real performance conditions — including making clear exit decisions when standards are not met.
• Ability to see genuine research potential beyond strong academic credentials.

Nice-to-have:

• Experience designing structured training programmes or bootcamps.
• Familiarity with graduate recruiting at top quantitative programmes.