Quantitative Developer - Cash Equities (Basé à London)

Jobleads
London
6 days ago
Applications closed

Related Jobs

View all jobs

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer - C#

Quantitative Developer C#.Net SQL Maths

Quantitative Developer C#.Net SQL Maths (Newcastle Upon Tyne)

Social network you want to login/join with:

col-narrow-left

Client:Location:

london, United Kingdom

Job Category:

Other

-

EU work permit required:

Yes

col-narrow-right

Job Views:

3

Posted:

05.05.2025

Expiry Date:

19.06.2025

col-wide

Job Description:

A leading global hedge fund is seeking a Quantitative Developer to join its high-performing Cash Equities team. The role involves developing and implementing quantitative trading strategies with a focus on cash equity markets. You will work closely with Portfolio Managers and quantitative traders, leveraging advanced algorithms, statistical models, and market data analysis to build and refine strategies deployed in production environments.

Key Responsibilities:

  • Develop and implement quantitative models and algorithms that drive trading decisions in cash equities.
  • Optimise strategy performance through innovative model development.
  • Partner with traders to analyse market dynamics, interpret valuations, and design next-generation models and analytics tailored to cash equity markets.
  • Contribute to the high-level architecture and optimisation of C++ and Python-based models used in various equity strategies.
  • Work closely with research teams to continuously enhance trading models and translate complex algorithms into efficient, production-ready code.

Skillset Requirements:

  • Proven experience in a quantitative development or software engineering role within a cash equities trading environment.
  • Expertise in applying advanced quantitative techniques to solve complex, data-driven problems.
  • Strong programming proficiency in C++ and/or Python, with a focus on high-performance, scalable systems.
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.

This is a unique opportunity to make an impact in a leading hedge fund's Cash Equities team, working alongside industry-leading professionals in a fast-paced environment. If you're a talented Quant Developer with experience in cash equities and a passion for financial markets, apply now to further your career in one of the industry’s most exciting roles.


#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.