Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Full Stack Quantitative Developer

South Bank
1 week ago
Create job alert

Senior Full Stack Quantitative Developer

Certain Advantage are hiring for a Senior Full Stack Quantitative Developer based in London on a hybrid basis.

This role is on an initial contract till the end of the year with a potential to be extended for a further 6 months.

Key Responsibilities

Design, develop, and maintain secure, scalable, and maintainable applications using Python and Azure cloud technologies for commodities trading solutions.
Leverage strong proficiency in Python, including use of numerical and scientific libraries such as Pandas, NumPy, SciPy etc.
Utilize a second strongly typed programming language (e.g., C#, C++, Rust, or Java) as needed.
Implement application architecture and DevOps best practices, including “Infrastructure as code”, Kubernetes, Docker, and automation testing frameworks.
Apply software design patterns to ensure robust, flexible, and future-proof solutions.
Collaborate with quant developers, analysts, and traders to translate business and quantitative requirements into technical specifications and software products.
Mandatory Skills

Extensive experience in Python application development, especially within trading, finance, or quantitative domains.
Proficiency with major Python numerical libraries (e.g., pandas, numpy, scipy, stats).
Experience with at least one additional strongly typed programming language (C#, C++, Rust, Java, etc.).
Strong background in Azure cloud application development, including security, observability, storage, and database resources.
Solid understanding of data engineering tools and technologies (Databricks, PySpark, Lakehouses, Kafka).
Advanced mathematics and quantitative analysis skills, ideally with hands-on experience in probabilistic modeling and the valuation of financial derivatives.
Domain expertise in derivatives within energy commodities-especially LNG, Gas, or Power Trading
Does this sound like your next career move? Apply today!
 
Working with Certain Advantage
 
We go the extra mile to find the best people for the job. If you’re hunting for a role where you can make an impact and grow your career, we’ll work with you to find it.
 
We work with businesses across the UK to find the best people in Finance, Marketing, IT and Engineering.
 
If this job isn’t for you, head to (url removed) and register for job alerts and career guidance tips

Related Jobs

View all jobs

Senior Full Stack Quantitative Developer

Quantitative Developer - Systematic Infrastructure - Multi-Strat Fund - $400k

Senior Quantitative Developer

Senior Quantitative Developer

Senior Data Scientist

Senior Data Scientist (Machine Learning & Advanced Analytics)

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.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.