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

Apply Now

Quantitative Developer Python SQL

Client Server
London
1 week ago
Create job alert
Overview

Quantitative Developer / Software Engineer (Python SQL) London / WFH to £90k

Are you a data savvy Quantitative Developer with strong Python skills looking for an opportunity to progress your career, working closely with traders on complex trading strategies with huge earning potential? You could be joining a Hedge Fund with over $10 billion under management. As a Quantitative Developer you'll implement, test and maintain pricing models and risk infrastructure, writing production quality Python code with a strong emphasis on readability, performance and testing across Fixed Income and Derivatives products including IR, FX, Bonds and Options, partnering with Quants to understand requirements and translate them into robust, well engineered solutions. You'll join a collaborative team and participate in code reviews, Pair Programming and technical design discussions. This is a great opportunity for a Quantitative Developer who is interested in working closely with the business and gain an in depth understanding of systematic trading.

WFH Policy
You'll join colleagues in the London office Tuesday to Thursday with Monday and Friday work from home; there's a friendly and collaborative environment with casual dress code and a range of facilities.

About You
  • You're a Software Engineer / Developer with strong Python coding skills including Pandas and other numerical libraries
  • You have experience with database languages such as SQL and KDB / other
  • You are familiar with CI/CD and DevOps tools
  • You're highly numerate with a good understanding of mathematics, comfortable working with large data sets
  • You have an interest in systematic trading systems and are keen to learn and progress in this area, previous financial services experience is nice to have
  • You're collaborate and have excellent communication and interpersonal skills
  • You're degree educated in a STEM discipline e.g. Computer Science or Mathematics
What's In It For You
  • Salary to £90k + bonus (c20-25%)
  • Pension and Private Healthcare
  • Hybrid working (x3 days in London office)
  • Impactful role working on cutting edge AI technology
  • Excellent career growth opportunities

Apply now to find out more about this Quantitative Developer / Software Engineer (React .Net Python) opportunity.

At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We\'re an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.


#J-18808-Ljbffr

Related Jobs

View all jobs

Quantitative Developer - Python

Quantitative Developer C++/ Python - London- World-Leading Hedge Fund

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.