At a Glance
- Tasks: Build impactful tools and workflows for trading and research with a collaborative team.
- Company: Join Squarepoint, a forward-thinking tech company in finance.
- Benefits: Competitive salary, growth opportunities, and a supportive work culture.
- Other info: Experience a transparent culture focused on continuous improvement and real-world impact.
- Why this job: Shape the future of technology while enhancing your skills in a dynamic environment.
- Qualifications: Strong programming skills in Python or C++, and a degree in a scientific discipline.
The predicted salary is between 36000 - 60000 £ per year.
We’re looking for pragmatic, motivated Quantitative Developers to join Squarepoint. You’ll work directly with quantitative researchers and other technologists to build high‑impact tools, analytics, and workflows that support trading, research, and risk processes. You don’t necessarily need a finance background; curiosity, solid engineering skills, and a product‑focused mindset matter most.
What You’ll Do
- Collaborate closely with quantitative researchers to understand their needs, define solutions, and deliver high‑value improvements.
- Design and implement Python libraries, pipelines, and services used to orchestrate workflows, compute analytics, price instruments, evaluate research, or calculate risk.
- Optimise and modernise existing components, improving performance, maintainability, and reliability.
- Drive iterative progress: ship MVPs, gather feedback, refine, and evolve solutions.
- Work alongside global Technology teams to ensure consistency and reuse of core components.
- Take full ownership of projects across the engineering lifecycle from design to deployment and monitoring.
What Makes You a Great Fit
- Mindset & Approach: Pragmatic, delivery‑oriented, and comfortable prioritising what drives real value. A self‑starter who takes ownership, communicates clearly, and collaborates effectively. Curious and adaptive - keen to learn, iterate, and improve.
- Technical Capabilities: Strong programming experience (Python, C++, or KDB+/q). Comfortable working in Linux environments. Familiar with modern development practices: version control, testing, CI, logging/monitoring. Good understanding of data structures, algorithms, and building clean, reliable code - and good debugging skills. Experience with data processing, storage, or analytics. Financial knowledge is not required, though interest is welcomed.
What You’ll Bring
- Degree in Computer Science, Engineering, or another scientific discipline.
- 3+ years of hands‑on software development experience.
- Excellent communication skills - able to work with both technical and non‑technical collaborators.
- A holistic view: you consider the broader system and organisational impact of your work.
- A practical approach: you keep things simple, avoid over‑engineering, and iterate with user feedback.
Why Join Us?
You’ll work in a highly collaborative team with strong engineering culture and visibility into real trading and research workflows. You’ll help shape the future of our Technology stack while growing your technical and domain skills. You’ll operate in an environment that values transparency, continuous improvement, and practical thinking.
Quantitative Developer employer: Squarepoint
As a Software Developer in the Market Data Integration team, you will thrive in a dynamic work culture that values collaboration and innovation. Our firm offers exceptional employee growth opportunities, including access to cutting-edge technology and training, while fostering a supportive environment where your contributions directly impact our market data services. Located in a vibrant city, we provide a unique advantage with our close ties to exchanges and vendors, ensuring you are at the forefront of the financial technology landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Developer
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Quantitative Developer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Squarepoint, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Squarepoint. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Squarepoint
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Squarepoint!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
