eFX Quant Analyst - VP
Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Aug 5, 2026. State Street scores A on the Alion truth index.
Who we are looking for
State Street’s electronic foreign exchange offering is a core component of our product range, making markets directly with counterparties, on exchanges and e-trading venues around the globe. Since inception we have sustained a considerable growth trajectory, becoming a significant player in this space by expanding our market making, algorithmic and benchmark execution capabilities.
We are looking to make an experienced VP-level hire in London to help sustain the continued growth of our eFX business. The successful candidate will have a proven track record of developing and deploying systematic eFX market-making and/or high-frequency trading strategies, applying statistical and machine-learning techniques to high-frequency, asynchronous datasets. They will join a successful, innovative and supportive team, with the opportunity to shape the strategic direction of our market-making platform. This role offers people-management responsibilities for the right candidate.
Why this role is important to us
You will join State Street Markets (SSM), our investment research and trading arm. SSM helps institutional clients preserve and enhance portfolio value by applying technology, optimising trading and connecting asset classes and markets globally. This role sits at the centre of that effort: improving the electronic pricing and risk-management models used in SSM’s FX business.
What you will be responsible for
As a senior member of the eFX Market Making team, you will:
- Own a significant portfolio of algorithms for electronic price making and risk management
- Lead, mentor and develop a team of quants, setting objectives and technical direction and supporting their professional growth
- Use public and proprietary data to identify new opportunities to generate P&L
- Drive research from prototype through to production, including backtesting, deployment and monitoring
- Analyse the behaviour of production trading models on an ongoing basis, identifying and delivering areas of improvement
- Partner with trading, technology and risk stakeholders to ensure models are robust, well-governed and effective in a low-latency environment
What we value
These qualities will help you succeed in this role:
Delivering results with integrity and speed
Creative thinking, motivated by challenging problems
A healthy scepticism about the robustness and generalisability of in-sample results
A working habit of first investigating simpler, parsimonious models
A desire to work within a collaborative, team-driven environment
Skills & experience
Demonstrable experience building or maintaining production quantitative trading systems
Experience leading, line-managing or mentoring a technical or quantitative team
The ability to complement technical high-frequency analysis with market insight and experience
Proficiency in a fast prototyping language, ideally Python (or Matlab, R or similar)
Working knowledge of an industrial-scale language such as Java or C++ (a plus)
Experience with agentic coding tools and AI coding assistants (a plus)
Postgraduate degree in a quantitative discipline, such as engineering, statistics, mathematics, physics or similar; PhD preferred
About State Street
Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.
We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.
As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.
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