Quantitative Developer

Barlowe LLP
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Science Quant Python - Fintech

Senior Data Scientist, Sports

Senior Data Scientist, Sports

Data Science & Machine Learning - Senior Associate - Asset Management

Data Science Lead

Data Science Lead

Do you want to tackle the biggest questions in finance with near infinite compute power at your fingertips

GResearch is a leading quantitative research and technology firm with offices in London and Dallas.

We are proud to employ some of the best people in their field and to nurture their talent in a dynamic flexible and highly stimulating culture where worldbeating ideas are cultivated and rewarded.

This role is based in our new Soho Place office opened in 2023 in the heart of Central London and home to our Research Lab.

The role

Engineering underpins our continued growth and success and we are committed to recruiting and developing the worlds best Engineers.

Our Quantitative Developers are the enablers of our success. They work sidebyside with our researchers to realise their ideas in global financial markets. They work at the bleedingedge with immense compute power at their fingertips to achieve our aim: predicting the future.

The core tech stack is C# and Python productionised in our own datacentres.

Areas of focus for these teams include:

  • Trading systems reliable and performant systems able to trade 24/6 for our customers with real money at stake
  • Modelling building core capabilities and assisting quant researchers in our cutting edge prediction capabilities
  • Simulation backtesting frameworks for validating the strategies our researchers produce and for assessing their ongoing performance
  • Research tooling frontend UX and workflow for our quant researchers
  • Performance and scalability optimising our trading and research systems to unlock new capabilities

To give a flavour of the work we do here are some of our recent projects:

  • Low level performance optimisations in our core simulation engine unlocking the next advances in quant research
  • Experimenting with alternative solvers in a core trade planning system
  • Integrating our high and low frequency systems for more optimal trading
  • Rearchitecting systems to provide a seamless path from research to production for machine learning models
  • Enabling largescale distributed training of machine learning models
  • Contributing back to open source projects

Who are we looking for

The ideal candidate will have the following the skills and experience:

  • A genuine interest in technology
  • Proven ability to engineer highquality software
  • Appreciation of architecture and engineering best practices
  • Experience of endtoend ownership of solutions from articulation through to delivery
  • Good understanding of fundamental algorithms and data structures
  • An interest in the quantitative finance and an understanding of the role engineering plays within the space
  • The ability to prioritise plan and deliver to demonstrably drive business results
  • The ability to proactively identify where we can improve and implement long term scalable solutions to drive business outcomes.
  • A proactive approach to learning staying ahead of the technology curve and identifying how we can adopt new technologies in the ways we work
  • Balanced judgement with the ability to evaluate different approaches and identify solutions for the benefit of the overall business
  • Adaptable communication styles and approaches tailored to their audience in order to convey compelling messages
  • The ability to understand the needs and challenges of others and present mutually beneficial solutions
  • A collaborative approach with the ability to build effective relationships across the business

Why should you apply

  • Highly competitive compensation plus annual discretionary bonus
  • Lunch provided (via Just Eat for Business) and dedicated barista bar
  • 35 days annual leave
  • 9 company pension contributions
  • Informal dress code and excellent work/life balance
  • Comprehensive healthcare and life assurance
  • Cycletowork scheme
  • Monthly company events

GResearch is committed to cultivating and preserving an inclusive work environment. We are an ideasdriven business and we place great value on diversity of experience and opinions.

We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section


Key Skills
CCTV,Computer Science,Corporate Marketing,E Learning,Arabic English Translation
Employment Type :Full-Time
Experience:years
Vacancy:1

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 Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.