Quantitative Developer

Venture Up
London
6 days ago
Create job alert

Python Quantitative Software Developer – London


*Please note this role cannot sponsor. Please do not apply if you are seeking sponsorship*


A Python Quantitative Software Developer is required for an exciting and innovative Software sports betting company based in London. The successful candidates will be working closely with the quantitative researchers and alongside other extremely talented and driven engineers to build and support systematic trading models. An interest in functional programming and its application in the real world would be useful. The roles would suit candidates with 3+ years experience and significant part of childhood spent hacking away in 8-bit assembly language. You will be joining a tight-knit team of research mathematicians, computer scientists and trading analysts at the top of their chosen fields.


Essential Skills


  • At least 3 years of software development experience, with a proven ability to work independently and innovate.
  • Proficiency in Python, particularly for numerical computing and machine learning
  • Particularly numpy, pandas (both must haves)
  • Good working knowledge of a fast language such as C / C++ / Rust.
  • Understanding of production-level system design and architecture.
  • Proficiency in SQL, working with structured data stored in psql databases and optimizing queries.
  • Experience working in environments where the speed of development is prioritised over formal processes.
  • An eagerness to collaborate with a diverse team of brilliant minds, contributing your own unique insights.
  • A self-starter attitude, with the confidence to take ownership of projects and experiment with new ideas.


Tech Stack


You’ll have the freedom to choose the tools and technologies that fit each problem best, but here’s a snapshot of what the company currently uses:


  • Python 3.10+ for most of their development.
  • C and Go for high-performance systems where needed.
  • Linux servers.
  • PostgreSQL for data storage.
  • ZeroMQ and RabbitMQ for backend communication.
  • Basic web front ends for internal tools.


Benefits:


  • Working alongside other extremely talented and driven engineers
  • Extremely lucrative salary, bonus up to 30% and benefits
  • Greenfield Python work, both challenging and rewarding


Send your CV for immediately review and further details.

Related Jobs

View all jobs

Quantitative Developer | Systematic Research

Quantitative Developer - C#

Quantitative Developer

Quantitative Developer

Quantitative Developer (python/react)

Quantitative Developer

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.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

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

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

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

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.