Quantitative AI Strategist

DRW Holdings, LLC.; Greater London; On-site; GBP 80,000 - 120,000; Full time

Job summary

A financial services firm in Greater London is seeking a Quantitative AI Strategist to join its quantitative analytics team. This front-office role focuses on building an AI-powered research platform aimed at enhancing trading and analytical insights. Candidates should have 3-7 years of experience in quantitative finance, solid programming skills in Python, and strong communication abilities to engage with trading desks. Competitive compensation and significant exposure to diverse asset classes are offered.

Qualifications

• 3-7 years of experience in a front-office quant or quantitative research role.
• Experience with signal generation and backtesting.
• Familiarity with Git and collaborative development workflows.

Responsibilities

• Prototype and validate quantitative workflows end-to-end.
• Write high-quality platform code and quantitative libraries.
• Enhance the platform’s analysis and reasoning capabilities.
• Continuously evaluate and improve platform use.
• Identify new use cases as AI technology evolves.

Skills

Quantitative analysis

Programming in Python

AI technologies understanding

Problem-solving ability

Strong communication skills

Education

Background in quantitative finance or related technical field

Job description

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.