The bridge between research and real-world trades
The Quant Implementation team sits at the heart of Marshall Wace’s systematic trading business. As a quant developer in the Quantitative Implementation team, you’ll design, develop, and maintain the alpha algorithms and portfolio construction processes that drive live trading — and resolve production challenges under demanding deadlines.
Your code has a direct impact on the real-world trades generated by our systematic models. You’ll own a large, complex codebase and be responsible for verifying research output and ensuring we can monetise our ideas efficiently in practice.
This is not a role where you’ll wait months to touch production. From day one, you’ll collaborate closely with multiple investment and research teams at one of Europe’s largest hedge funds, gaining exposure to a range of investment styles and asset classes.
What you’ll work on
Alpha algorithms and portfolio construction — design, build, and maintain the systems that implement systematic trading strategies in production
Research-to-production pipeline — translate quantitative research ideas into robust, scalable production code
Live trading systems — resolve real-time trading challenges and support mission-critical systems under demanding deadlines
Data infrastructure — build large-scale data processing pipelines and time-series analysis tooling
Performance engineering — design low-latency systems with a focus on concurrency, memory management, and throughput optimisation
DevOps and production support — CI/CD, containerisation, monitoring, and operational reliability of trading infrastructure
Example projects
Implementing a new alpha algorithm from research specification through to live trading, validating output at every stage
Redesigning a portfolio construction process to handle additional asset classes and optimisation constraints
Profiling and optimising a high-throughput data pipeline to reduce latency across the signal generation chain
Building monitoring and alerting for production trading systems to catch issues before they affect live positions
What we’re looking for
Academic Achievement
Excellent academic record from a top-tier university. Minimum Master’s degree in a STEM discipline — computer science, mathematics, physics, engineering, or similar.
Experience
We welcome recent graduates and early-career developers with up to 3 years of relevant experience. A broad understanding of quantitative finance and previous exposure to the field — through industry, academic research, or projects — is expected.
Technical profile
You’re an expert-level software engineer and programmer (Python, MATLAB, C++, or Java) with strong quantitative foundations — probability, statistics, linear algebra, numerical methods. You write clean, testable, performant code and you’re comfortable with low-latency system design, Linux, and modern DevOps tooling. You understand how financial markets work — equities, futures, options, or fixed income.
Mindset
You translate research ideas into production systems, not prototypes
You work quickly and accurately under pressure
You communicate clearly with quants, traders, and researchers
You take ownership of code quality, performance, and reliability
Programme structure
Location: London
Team: Quant Implementation, within Systematic Investment
Development: fortnightly internal talks, mentoring, structured development programme, access to advanced technology and significant computing resources
Environment: collaborative, shared codebase — best practices are applied across teams to accelerate research and drive business growth
