Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

High Frequency Quant Strategist/ London

Eka Finance
London
11 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Quant Engineer - Investment banking

Quantitative Researcher (Machine Learning)

Quantitative Researcher (Machine Learning)

First Team Data Scientist

First Team Data Scientist

First Team Data Scientist

Leading systematic hedge fund are looking to hire a high-frequency strategist with a strong background in statistics and data analysis to strengthen their research efforts in liquid futures and cash equity markets.



Role:-


You will be responsible for developing and driving your own research agenda across all aspects of trading, from alpha generation to portfolio construction and execution. Specific responsibilities will include:



  • Conducting in-depth quantitative research into the behaviour of liquid financial markets.
  • Developing and back-testing novel and innovative alpha signals to predict the movements of markets over time horizons spanning from minutes to days.
  • Customising and tuning machine learning algorithms to optimize alpha accuracy
  • Improving trading logic through experimentation and optimization.
  • Conducting research to improve the ability to monetize and execute alpha signals.
  • Working with the technologists to help improve the trading platform and infrastructure.



Requirements:-



  • A strong academic background, with a degree in a quantitative subject (e.g. Mathematics, Physics, Engineering, Computer Science, Economics, Finance) from a leading university.
  • Further degrees or postdoctoral roles are beneficial although not a requirement.
  • Experience undertaking in-depth quantitative research for trading in either futures or cash equity markets.
  • Experience in linear and non-linear machine learning algorithms.
  • Hands-on experience of working with large data sets.
  • An interest in financial markets modeling and investing.
  • A deep understanding of statistics and an ability to apply it to real-world problems.
  • Intermediate skills in at least one programming language (e.g. Python, Java, C, C++).
  • The ability to communicate complicated ideas clearly and concisely.


Apply:-


Please send a PDF CV to

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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.