Quantitative Researcher – Crypto HFT

Algo Capital Group
London, England
11 months ago
Applications closed

Related Jobs

View all jobs

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

DMPK Lead (PBPK Specialist), London, Lausanne

Isomorphic Labs United Kingdom

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
Posted
22 May 2025 (11 months ago)

Quantitative Researcher – Crypto HFT

Apply advanced mathematical models and statistical techniques to develop alpha-generating strategies in crypto. A world-leading proprietary trading fund is seeking Quantitative Researchers to develop and execute high-frequency trading strategies in the digital asset space. You’ll collaborate with a multidisciplinary team of engineers and quants to deploy real-time, scalable trading solutions and have the autonomy to implement your own trading strategies.


What you’ll do:

  • Design and implement High-frequency trading strategies for digital assets.
  • Work closely with infrastructure teams to optimize latency and execution.
  • Leverage data to continuously refine strategies and stay ahead of market trends.


What’s in it for you?

  • Be immersed in cutting-edge High-frequency trading systems and strategies for the crypto space.
  • Competitive salary with profit-sharing opportunities based on performance.
  • A dynamic and fast-paced environment with tier-1 infrastructure access.


Key Skills & Knowledge:

  • 4+ years’ experience with Python.
  • Extensive expertise in mathematics and statistics, with a particular focus on statistical modelling and signal generation.
  • Experience as a crypto high-frequency quantitative trader, proven multi-year track record of consistent PnL, and a 2+ Sharpe ratio.


Reach out at to discuss the opportunity further, or please apply now.

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

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

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

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.

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.

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.