At a Glance
- Tasks: Lead the development of back-testing frameworks and algorithmic trading systems.
- Company: Join a top systematic trading firm with a global presence.
- Benefits: High compensation, relocation costs covered, and remote work options after one year.
- Other info: Opportunity to mentor junior developers and grow in a dynamic environment.
- Why this job: Make an impact in trading tech while collaborating with talented quants and traders.
- Qualifications: 4-5 years of Python experience in trading or finance; strong problem-solving skills.
The predicted salary is between 36000 - 60000 £ per year.
Join a leading systematic trading firm with a strong presence across equities and futures. We’re looking for a hands-on Python Quant Developer to lead and expand the centralised back-testing and research infrastructure that powers all systematic strategies.
The Role
This position is ideal for someone who began their career as a software developer and has evolved into a quantitative developer, combining deep technical expertise with a strong grasp of trading logic. You’ll take ownership of building and optimising back-testing frameworks, APIs, and algorithmic trading systems, ensuring the team’s research and execution capabilities remain best-in-class. While the primary focus is on engineering and infrastructure, you’ll also contribute to strategy development and idea testing from time to time, collaborating closely with systematic traders.
Key Responsibilities
- Lead the design and optimisation of back-testing and research infrastructure for systematic strategies
- Build and maintain APIs and automation tooling to support trading and research workflows
- Develop and scale robust systems for mid-frequency equities and futures trading
- Collaborate with quants and traders to implement and refine algorithmic trading and bot systems
- Contribute to occasional strategy research and prototype development
- Manage and mentor junior developers, ensuring high coding and testing standards
Requirements
- 4–5 years of Python development experience in trading, finance, or other data-heavy environments
- Proven experience building back-testing systems, APIs, or automation pipelines
- Strong understanding of data structures, algorithms, and software engineering best practices
- Track record of designing scalable, production-grade systems
- Excellent problem-solving, collaboration, and communication skills
Nice to Have
- Experience with NumPy, Pandas, Cython, or Numba
- Exposure to market microstructure, risk modelling, or quantitative research
- Experience developing and maintaining live trading bots or algo execution systems
- Background in mentoring or technical leadership within a quant or trading team
Quantitative Developer employer: Harrington Starr
Harrington Starr is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. As a Dynamics CRM Developer, you will have the opportunity to work with cutting-edge technologies like Azure and Power Platform, while benefiting from a culture that prioritises professional growth and development. Located in a vibrant area, the company fosters a supportive atmosphere that encourages creativity and teamwork, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Developer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Harrington Starr!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Quantitative Developer at Harrington Starr.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Harrington Starr.
✨Apply Directly through Our Website
When you find a suitable opening like Quantitative Developer at Harrington Starr, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
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 Harrington Starr, 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 Harrington Starr. 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 Harrington Starr
✨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 Harrington Starr!
✨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.
