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For Companies At a Glance
- Tasks: Join a cutting-edge AI/ML project, designing systems for investment platforms.
- Company: Work with a leading hedge fund on innovative financial technology.
- Benefits: Enjoy a hybrid work model and competitive day rates.
- Why this job: Shape the future of finance while collaborating with top experts in a dynamic environment.
- Qualifications: Strong Python skills and knowledge of machine learning and quantitative finance required.
- Other info: 12-month contract starting July 2025, ideal for those passionate about tech and finance.
The predicted salary is between 43200 - 72000 £ per year.
Location: London, UK (Hybrid)
Contract Type: 12-Month Contract (Inside IR35)
Start Date: July 2025
About the Role
We are partnering with a leading hedge fund embarking on a cutting-edge greenfield initiative to build a next-generation AI/ML-driven investment platform. This is a rare opportunity to join at inception and shape the architecture, tooling, and models that will drive alpha generation and risk management for years to come.
As a Quant Developer, you will work at the intersection of quantitative research, machine learning, and software engineering. You will collaborate with quants, data scientists, and portfolio managers to design and implement scalable systems for data ingestion, model training, and real-time signal deployment.
Key Responsibilities
- Design and develop robust, high-performance systems for AI/ML model development and deployment.
- Collaborate with quantitative researchers to translate trading strategies into production-ready code.
- Build and maintain data pipelines for structured and unstructured financial data.
- Implement backtesting frameworks and simulation environments.
- Optimise model inference and execution latency for real-time trading.
- Contribute to architectural decisions and technology stack selection for the greenfield platform.
Required Skills & Experience
- Strong programming skills in Python, with experience in production-grade systems.
- Solid understanding of machine learning workflows, including model training, validation, and deployment.
- Experience with quantitative finance, including time series analysis, alpha modelling, or risk analytics.
- Familiarity with cloud infrastructure (e.g., AWS, GCP) and containerisation (Docker, Kubernetes).
- Proficiency with data engineering tools.
- Experience working in fast-paced, collaborative environments with agile methodologies.
Nice to Have
- Prior experience in a hedge fund, prop trading firm, or investment bank.
- Exposure to reinforcement learning, deep learning, or LLMs in financial contexts.
- Knowledge of market microstructure and execution algorithms.
Contract Details
- Duration: 12 months
- Start Date: July 2025
- Location: London (Hybrid working model)
- IR35 Status: Inside IR35
- Day Rate: Competitive, based on experience
If this could be interesting for you, please apply at your earliest convenience. We look forward to hearing from you.
Quant Developer employer: Glocomms
Contact Detail:
Glocomms Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Developer
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning, especially as they relate to finance. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Network with professionals in the quantitative finance space. Attend meetups, webinars, or conferences where you can connect with quants and developers. This can provide insights into the role and potentially lead to referrals.
✨Tip Number 3
Brush up on your Python skills, particularly in relation to production-grade systems. Consider working on personal projects or contributing to open-source projects that showcase your ability to implement scalable systems.
✨Tip Number 4
Prepare to discuss your experience with cloud infrastructure and containerisation tools. Be ready to explain how you've used these technologies in past projects, as this will be crucial for the role.
We think you need these skills to ace Quant Developer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative finance, machine learning, and software engineering. Use specific examples that demonstrate your programming skills in Python and any experience with cloud infrastructure or data engineering tools.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI/ML and your understanding of the hedge fund industry. Mention how your skills align with the responsibilities of the Quant Developer role and express your enthusiasm for contributing to a greenfield project.
Highlight Relevant Projects: If you have worked on projects involving model training, backtesting frameworks, or real-time trading systems, be sure to include these in your application. Detail your role in these projects and the impact they had on the overall outcome.
Showcase Collaboration Skills: Since the role involves working closely with quants and data scientists, emphasise your experience in collaborative environments. Provide examples of how you've successfully worked in teams to achieve common goals, especially in fast-paced settings.
How to prepare for a job interview at Glocomms
✨Showcase Your Technical Skills
As a Quant Developer, strong programming skills in Python are essential. Be prepared to discuss your experience with production-grade systems and demonstrate your understanding of machine learning workflows during the interview.
✨Understand the Financial Context
Familiarise yourself with quantitative finance concepts such as time series analysis and alpha modelling. Being able to relate your technical skills to financial applications will impress the interviewers.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with quants and data scientists, be ready to discuss examples of past collaborations. Highlight your experience in agile environments and how you contributed to team success.
✨Demonstrate Problem-Solving Abilities
Expect technical questions that assess your problem-solving skills, especially in optimising model inference and execution latency. Prepare to walk through your thought process and any relevant projects you've worked on.
