Quant Developer (Python or C++ and Machine Learning)

CASPIAN ONE
London
7 months ago
Applications closed

Related Jobs

View all jobs

C# Developer - London- C#, SQL, Machine Learning, Quant/ Systematic Trading

Vice President Data Science

Data Scientist

Data Scientist

Lead Quant Strategist Artificial Intelligence (AI) Research Engineer

Machine Learning Engineer

We are seeking an exceptionally talented Quantitative Developer to join a growing, high-performing systematic investment team in London. This is a unique opportunity to be part of a small, collaborative, and entrepreneurial group focused on building critical trading infrastructure in the fast-paced world of systematic equities trading.



Make sure to apply with all the requested information, as laid out in the job overview below.

This role is ideal for a self-starter who thrives in a dynamic environment, with opportunities for career growth and exposure to cutting-edge technology and innovative trading strategies. We are looking for the best of the best, and there is no set budget for this role. If you are passionate about building systems for high-impact trading and want to be part of a top-tier hedge fund environment, we want to hear from you!


Key Responsibilities:

  • Assist in building systems for implementing trading algorithms that the team is actively researching.
  • Design, code, and maintain the team’s trading infrastructure.
  • Develop and maintain tools to support systematic trading infrastructure.
  • Conduct data analysis and generate both live and historical analytical reports.
  • Stay up-to-date with the latest technologies and tools, including technical libraries and computing solutions.
  • Collaborate closely with the Senior Portfolio Manager (SPM) and trading group, engaging transparently in the entire investment process.


Preferred Technical Skills:

  • Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Applied Mathematics, Statistics, or a related STEM field.
  • 5+ years of experience with Python and C++.
  • Strong understanding of computer hardware and optimization techniques.
  • Proven experience in building out production trading infrastructure.
  • Experience creating quantitative tools for research purposes.
  • Strong communication, analytical, and quantitative skills.
  • Ability to manage and complete projects independently.


Preferred Experience:

  • Open to candidates with strong backgrounds from both finance and technology sectors.
  • Experience working directly with systematic trading teams or building tools for quantitative research is highly desirable.


This role requires 5 days a week in the office, providing you the chance to work closely with top-tier professionals in a hands-on, interactive environment. If you’re ready to bring your skills and experience to a challenging yet rewarding role with a leading hedge fund, apply now!


Note:This position does not have a predetermined budget, and we are seeking only the most talented candidates who can deliver exceptional results.

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.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.