Senior Quantitative Developer (Basé à London)

Jobleads
Holloway
1 month ago
Create job alert

DRWis a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it.DRWis a place of high expectations, integrity, innovation and a willingness to challenge consensus.

DRW is looking for an exceptionalSenior Quantitative Developerwith expertise in core quantitative libraries development and their integration with external pricing and risk systems and tools to join a team of highly talented quants tasked with building a proprietary multi-asset class analytics platform.

Your role will focus on all the most technical aspects of the development of the core quantitative library including its performance, testing, stability, API-design, core data structures, multi-platform and multi-language support, while working closely with the quantitative analysts that developed the library, and the software engineers responsible for the analytics platform. Your work will be used throughout the organization on a daily basis by traders, risk managers, and back office analysts.

To qualify for this role, you:

  • Have at least 5 years of professional experience with modern C++
  • Have working knowledge of fundamental concepts of financial analytics (options pricing, curve bootstrapping, model calibrations, etc)
  • Have extensive hands-on experience with Python, C#
  • Have hands-on experience integrating analytics libraries with large scale software systems and services
  • Have experience with optimizing software for performance
  • Have practical experience designing API for embedded libraries
  • Have experience developing and providing front-line support for high-performance financial analytics code
  • Have created and supported user-facing interactive, UI-based tools for pricing, PnL and Risk calculations and market analysis
  • Have strong communication and collaboration skills with the ability to work within a multi-disciplinary team that includes traders, software engineers, and quants
  • Have strong sense of ownership of work and the ability to work independently and under pressure
  • Have experience with SQL / NoSQL / Redis / RabbitMQ / OLAP

Bonus points if you have:

  • Experience with interfacing C++ code with higher-level languages (e.g. Python, Java, C#) using SWIG or similar tools
  • Experience with Adjoint Algorithmic Differentiation
  • Experience with other programming languages such as C# (highly desirable), Java and VBA
  • Experience with statistical analysis and working with large datasets provided in relational or key-value databases
  • Have a Ph.D. in a quantitative field such as physics, mathematics, computer science, operations research or financial engineering

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

#J-18808-Ljbffr

Related Jobs

View all jobs

Quantitative Developer HFT

Senior Product Manager - Alternative Payment Methods (Basé à London)

Python Developer

Senior UX Designer

Policy Analyst

Regional Finance Director

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 for Non‑Technical Professionals: Where Do You Fit In?

Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.

Data Science vs. Data Mining vs. Business Intelligence Jobs: Which Path Should You Choose?

Data Science has evolved into one of the most popular and transformative professions of the 21st century. Yet as the demand for data-related roles expands, other fields—such as Data Mining and Business Intelligence (BI)—are also thriving. With so many data-centric career options available, it can be challenging to determine where your skills and interests best align. If you’re browsing Data Science jobs on www.datascience-jobs.co.uk, you’ve no doubt seen numerous listings that mention machine learning, analytics, or business intelligence. But how does Data Science really differ from Data Mining or Business Intelligence? And which path should you follow? This article demystifies these three interrelated yet distinct fields. We’ll define the core aims of Data Science, Data Mining, and Business Intelligence, highlight where their responsibilities overlap, explore salary ranges, and provide real-world examples of each role in action. By the end, you’ll have a clearer sense of which profession could be your ideal fit—and how to position yourself for success in this ever-evolving data landscape.