Quantitative Developer - Low Latency

Stanford Black Limited

Bedford, England

10 months ago

Applications closed

Related Jobs

View all jobs

KDB Developer

James Joseph Associates Broad Street, Greater London, City And County Of the City Of London, United Kingdom

£120,000 – £150,000 pa

Data Scientist

Randstad Technologies Recruitment London, United Kingdom

AI Engineer - FDE (Forward Deployed Engineer)

Databricks London, United Kingdom

Genomic Data Scientist in Rare Disease (we have office locations in Cambridge, Leeds & London)

Genomics England Canary Wharf, London, E14 5AB, United Kingdom

£55,000 – £100,000 pa

PKPD Modelling Lead, London

Isomorphic Labs London, United Kingdom

PKPD Modelling Lead, Lausanne

Isomorphic Labs United Kingdom

Posted: 1 Jul 2025 (10 months ago)

Save job

Create job alert

Applications closed

I'm working with the CTO of a modern, market-leading crypto firm who are on a mission to build the most advanced trading infrastructure for digital assets and power global liquidity across CeFi and DeFi.

They're looking for an exceptional Quantitative Developer to join a newly formed high-frequency trading team. You will work at the cutting edge of low-latency trading and DeFi integration, while helping to build our new Rust-based trading platform from the ground up.

You'll join a team led by a renowned HFT expert and contribute directly to the design and scale-up of one of the most ambitious crypto trading systems in the industry.

Role:

Develop high-performance trading algorithms for low-latency and high-frequency strategies.
Build and maintain front-office systems covering real-time data, risk, live trading, and post-trade workflows.
Integrate on-chain data sources by connecting to DeFi protocols and real-time feeds.
Design and run backtests to validate and refine your models.
Implement risk controls like capital limits and stop-loss mechanisms.
Monitor live systems and troubleshoot production issues in real time.

Experience:

2-8 years of commercial experience building HFT or trading systems.
Strong understanding of order books, order state machines, and market microstructure.
Excellent programming skills with a focus on performance and low-level optimization.
Proficiency in Rust, or strong C/C++ experience with willingness to code in Rust full-time.
Experience or interest in crypto markets is a strong plus.

Perks:

A leading role in a greenfield HFT project in the crypto space.
International team and work environment.
Top-tier equipment: MacBook, 4K monitor, noise-canceling headphones, and more.
100% health coverage
Team offsites and social events.
Future perks: gym memberships, international mobility, and more on the way.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Apr 9, 2026

Products

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Mar 24, 2026

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

Feb 10, 2026

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.