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For Companies At a Glance
- Tasks: Lead the development of a cross-asset monetisation framework for high-frequency trading.
- Company: Join a leading hedge fund known for its innovative systematic trading strategies.
- Benefits: Enjoy global mobility, flexible working options, and a chance to shape the future of trading.
- Why this job: Make a real impact on firm-level returns while working in a dynamic, cutting-edge environment.
- Qualifications: 5+ years in quant roles with expertise in portfolio optimisation and strong coding skills.
- Other info: Opportunity to mentor a team and work directly with top management.
The predicted salary is between 72000 - 108000 ÂŁ per year.
The Straight‑Up Bit - Who we’re hiring for
Yes, it’s a hedge fund. Yes, they’re one of the biggest systematic shops you’ve almost definitely heard about. Yes, they already run serious intraday equity flow across the globe.
Now let’s talk about the gap they haven’t filled… yet.
The Role
This firms’ HFT unit is sitting on a warehouse of alpha from researchers across the HFT business. What they don’t currently have is a cross-asset Monetisation Stack - the layer that turns raw signals into real‑time, risk‑balanced positions. That’s where you come in. As the Lead Monetisation Quant you will:
- Pipe every alpha stream through a clean, latency‑aware weighting engine.
- Build an optimiser for intraday books, factoring capacity, impact and microstructure quirks.
- Own live PnL attribution and feedback to researchers & traders.
- Hire and mentor the team that will scale this from “clever prototype” to “firm‑wide PnL driver”.
Green‑field. No legacy code. You set the standards.
The Opportunity
All the levers, none of the red tape – direct line to the head of the HFT business, a chance to own the project and develop a cross-asset monetisation framework (starting with Equity and expanding out). Massive surface area – every equity alpha the firm produces flows through your framework; your tweaks move firm‑level returns. Global flexibility – London HQ initially, but with global mobility in the future.
About You
~5+ yrs quant experience with at least 2 yrs designing portfolio construction / optimisation for intraday / short‑term equities. Fluent in statistics & ML (shrinkage, online learning, factor models) and market microstructure (spreads, impact, queue dynamics). Polyglot coder who can prototype in Python and drop to C++ when speed matters. Comfortable leading 3–5 quants, owning architecture and managing engineering collaboration with technology.
Interested? Drop me a line: (or hit “Apply” and then email me so I know you’re not a bot). We’ll keep it confidential.
(If you’re looking for pure alpha research roles or a pod seat, this isn’t it (but we should still chat... see above contact address). If you want to build the engine for alpha combination to make serious impact on already serious PnL, let’s talk.)
Lead Quant Researcher - Monetisation employer: Augmentti
Contact Detail:
Augmentti Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Quant Researcher - Monetisation
✨Tip Number 1
Network with professionals in the hedge fund and quantitative research space. Attend industry conferences or meetups where you can connect with people who work at similar firms. This can help you gain insights into the company culture and potentially get a referral.
✨Tip Number 2
Familiarise yourself with the latest trends in quantitative finance, particularly in portfolio optimisation and market microstructure. Being able to discuss recent developments or innovations during your conversations can set you apart from other candidates.
✨Tip Number 3
Prepare to demonstrate your coding skills in Python and C++. Consider working on personal projects or contributing to open-source projects that showcase your ability to prototype and optimise algorithms relevant to intraday trading.
✨Tip Number 4
Be ready to discuss your leadership experience and how you've mentored others in previous roles. Highlight specific examples of how you've built teams or improved processes, as this will be crucial for the Lead Quant Researcher position.
We think you need these skills to ace Lead Quant Researcher - Monetisation
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your quant experience, particularly in portfolio construction and optimisation for intraday equities. Use specific examples that demonstrate your fluency in statistics, machine learning, and market microstructure.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the opportunity to build a cross-asset monetisation framework. Mention your leadership experience and how you plan to mentor a team of quants, as well as your coding skills in Python and C++.
Showcase Relevant Projects: If you have worked on projects related to alpha streams or intraday trading, be sure to include these in your application. Detail your contributions and the impact they had on PnL, as this will demonstrate your capability to drive results.
Follow Up: After submitting your application through our website, consider sending a follow-up email to express your continued interest in the position. This can help keep your application top of mind for the hiring team.
How to prepare for a job interview at Augmentti
✨Showcase Your Quant Experience
Make sure to highlight your 5+ years of quant experience, especially your work in portfolio construction and optimisation for intraday equities. Be prepared to discuss specific projects where you've successfully implemented these skills.
✨Demonstrate Technical Proficiency
Since the role requires fluency in statistics, machine learning, and coding, be ready to discuss your experience with these areas. Bring examples of how you've used Python and C++ in past projects, particularly in high-speed environments.
✨Discuss Leadership and Mentoring
As a Lead Quant, you'll be expected to manage a team. Share your experiences in leading quants, mentoring junior staff, and how you’ve fostered collaboration between research and technology teams.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving abilities. Think about challenges you've encountered in previous roles and how you overcame them, particularly in relation to market microstructure and PnL attribution.
