At a Glance
- Tasks: Join our team to build AI-powered analytics for traders and researchers.
- Company: Dynamic firm at the forefront of quantitative finance and AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with exposure to diverse asset classes and cutting-edge technology.
- Why this job: Make a real impact in finance by leveraging AI to enhance trading strategies.
- Qualifications: Experience in quantitative finance and strong programming skills in Python required.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a Quantitative AI Strategist to join our quantitative analytics team. This is a front-office role at the intersection of quantitative finance, AI, and product development — focused on building and evolving the firm’s AI-powered research and analytics platform. The platform helps traders, researchers, analysts, and risk managers move from questions to actionable insight by unifying analytics, data, and research. Your job is to make it indispensable — by working directly with trading desks to understand their workflows, building the quantitative and AI capabilities they need to generate better ideas and make better decisions, and partnering with software engineers to deliver them at production quality.
You will have broad exposure across asset classes, desks, and problem types — from signal generation and backtesting to risk analysis and research analytics — while working at the frontier of applying AI to quantitative finance. The ultimate goal is to help the firm generate more revenue through AI-assisted trading and research.
The ideal candidate will be able to:
- Work directly with trading desks across asset classes and other stakeholders across the firm to identify high-value use cases for the platform.
- Determine the right balance between AI autonomy and structured tooling — deciding what the AI should reason through on its own, what instructions and domain knowledge it needs, and what purpose-built code it should call — and build accordingly.
- Work with front-office stakeholders to turn desk needs into well-defined quantitative problems/workflows, and collaborate with technology teams and quantitative researchers to deliver solutions.
Key Responsibilities
- Prototype and validate quantitative workflows end-to-end — from data retrieval and signal construction through to strategy evaluation, PnL simulation, testing, and risk/scenario analysis — while defining how the AI should interact with data sources, analytics libraries, desk-specific tools, etc., and work with engineers to deliver them as production platform capabilities.
- Write high-quality platform code and quantitative libraries — including code designed to be called and understood by AI, with clear interfaces, documentation, and instructions to AI.
- Enhance the platform’s ability to reason about markets, interpret financial data, and produce reliable, contextually aware analysis across products and markets.
- Continuously evaluate how the platform is used, identify where it excels and where it falls short, and drive improvements that deliver measurable value to trading and research workflows.
- Engage with stakeholders across the firm — trading desks, risk management, researchers, new joiners, and others — to discover emerging use cases and adapt the platform’s capabilities accordingly.
- Proactively identify new use cases and capabilities as AI technology evolves.
- Act as the first line of quantitative support for platform users — diagnosing issues, feeding insights back into platform development, and ensuring a high-quality user experience.
Qualifications and Experience
- Background in quantitative finance, financial engineering, applied mathematics, statistics, physics, computer science, or a related technical field.
- 3–7 years’ experience in a front-office quant, strategist, or quantitative research role, ideally with exposure to multiple asset classes.
- Solid understanding of financial markets, pricing/risk methodologies, and PnL attribution.
- Experience building or contributing to internal analytics platforms or tools used by traders and researchers.
- Experience with signal generation, backtesting, or systematic strategy development.
- Strong programming skills in Python.
- Familiarity with Git and collaborative development workflows.
- Familiarity with AI technologies and their application to quantitative workflows is a strong plus.
- Experience building AI agents is a strong plus.
- Excellent communication skills — able to engage directly with trading desks to understand their needs, formalize them into quantitative specifications, and collaborate effectively with software engineers.
- Strong problem-solving ability, intellectual curiosity, and comfort working across team boundaries in a fast-paced trading environment.
- Strong ability to quickly learn and adapt to new technologies — particularly important given the rapid pace of development in AI.
Quantitative AI Strategist employer: DRW Holdings, LLC.
As a Quantitative AI Strategist at our firm, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. We offer competitive benefits, including professional development opportunities and exposure to cutting-edge AI technologies in the heart of the financial district, ensuring you are at the forefront of quantitative finance. Join us to make a meaningful impact by transforming data into actionable insights while working alongside talented professionals dedicated to excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative AI Strategist
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the game. You never know when a casual chat could lead to your next big opportunity.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your quantitative projects, AI models, or any relevant work. This is your chance to demonstrate what you can bring to the table, so make it shine and share it during interviews or networking events.
✨Tip Number 3
Prepare for those interviews! Research the company and its products, especially how they use AI in finance. Be ready to discuss how your experience aligns with their needs and come armed with questions that show your interest and understanding of their work.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talent like yours. Keep an eye on our job postings and make sure to submit your application directly — it’s the best way to get noticed by our hiring team.
We think you need these skills to ace Quantitative AI Strategist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Quantitative AI Strategist. Highlight your experience in quantitative finance and any relevant AI projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI in finance and how you can contribute to our platform. Be specific about your experiences and how they relate to the job description.
Showcase Your Technical Skills:Since this role requires strong programming skills, make sure to mention your proficiency in Python and any experience with Git. If you've built AI agents or contributed to analytics platforms, we want to hear about it!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at DRW Holdings, LLC.
✨Know Your Quantitative Stuff
Brush up on your quantitative finance knowledge, especially around signal generation and risk analysis. Be ready to discuss specific examples from your past experience where you successfully applied these concepts.
✨Understand AI's Role
Familiarise yourself with how AI can enhance quantitative workflows. Prepare to explain how you've used AI technologies in previous roles or how you envision them being applied in this position.
✨Communicate Clearly
Since you'll be working closely with trading desks, practice articulating complex quantitative problems in simple terms. Think of examples where you effectively communicated technical details to non-technical stakeholders.
✨Show Your Problem-Solving Skills
Be prepared to tackle hypothetical scenarios during the interview. Think through how you would approach identifying high-value use cases for the platform and demonstrate your analytical thinking process.
