C++ Quant Developer - Systematic Equities | London- Leading Multi-Strategy IM

Oxford Knight

London

1 year ago

Applications closed

Related Jobs

View all jobs

Data Engineer

Senior Data Engineer (2 days onsite in London)

Data Engineer (Snowflake, SQL, Python)

Data Engineer - Azure

Data Scientist (Globally Renowned Retail Group)

GCP Data Engineer

C++ Quant Developer - Systematic Equities | LondonSalary:£150-350k TC

Summary

Superb opportunity to join one of the world's most prestigious hedge funds as a Quant Developer within Systematic Equities. This is a high impact role, within a small, entrepreneurial investment team, where you will be building critical trading infrastructure in a highly collaborative environment.

Working directly with the senior PM and quant researchers, your primary focus will be designing, coding, and maintaining tools for the systematic trading infrastructure. You'll develop data engineering and prediction tools for the systematic trading of equities, implement technology to enable large-scaleputational efforts in quant research, and build and maintain robust data pipelines and databases.

To succeed in this role, you will have exceptionalmunication skills,fortable facing off to the business, with a real drive for collaborative success.

Skills and Experience Required

5+ years' experience with a strongputer science or engineering background Expert-level C++ programming experience, plus advanced Python Track record in Linux-based development Experience with DevOps functions ( Google Cloud, Airflow, InfluxDB, Grafana) Degree (Masters or PhD preferred) inputer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field, from a top-tier university

Desirable
Knowledge of machine learning and statistical techniques and related libraries Experience as a quantitative developer supporting an intraday (or faster) system Experience with the development practices of large tech (Google/Meta, etc.) or finance firms
Benefits & Incentives:
Significant salary + bonus + benefits Dynamic, fast-paced environment; excellent career growth opportunities Collaborative culture and an energetic, dynamic engineering atmosphere Build and share knowledge with the smartest engineers in the industry

Contact
If you think you are a good fit for the role and would like further information, please contact:

Dominic Copsey

+44 (0) 203 475 7193
linkedin/in/dom-copsey-586478143/

Job ID z0NdBEIkGpAD

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.

Jan 18, 2026

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jan 13, 2026

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Jan 6, 2026

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.