Quantitative Developer

Broadbean Technology
Greater London
9 months ago
Applications closed

Related Jobs

View all jobs

Quantitative Analyst

Data Scientist

Snr Technical Apps Specialist - Quantitative Risk Management

Snr Technical Apps Specialist - Quantitative Risk Management

Environmental Data Analyst

2x Senior Data Engineer (Financial Services)

Robert Half are seeking an experienced Quantitative Developer to support the buildout of an automated trading system on an inital 3 months contract.

Responsibilities:

The ideal candidate will be proficient in backend Python development and have direct experience integrating with the Interactive Brokers API.

  • Collaborate on the development of a fully automated trading system using Python and the Interactive Brokers API

  • Translate trading strategies and data logic into clean, production-ready code

  • Post-setup, focus will shift to:

    • System optimization for performance and reliability

    • Enhancing reporting and monitoring capabilities

    • Designing and implementing robust risk management controls

Requirements:

  • Proven experience building automated trading systems

  • Strong Python programming skills (backend focus)

  • Direct experience with the Interactive Brokers API is essential

  • Strong understanding of trading workflows, data pipelines, and risk controls

  • Able to work independently and deliver within tight timelines

Organisation:

  • 3 months initially, with potential for extension

  • Outside IR35

  • 5 days per week, based out of the London office

Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to diversity, equity and inclusion. Suitable candidates with equivalent qualifications and more or less experience can apply. Rates of pay and salary ranges are dependent upon your experience, qualifications and training. If you wish to apply, please read our Privacy Notice describing how we may process, disclose and store your personal data:roberthalf.com/gb/en/privacy-notice.

YW5kcmUuZ2FyZGVuZXJtY2ZhcmxhbmUuOTk4MDQuMTIyNzFAcmhpLmFwbGl0cmFrLmNvbQ.gif

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.