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- Tasks: Design and maintain Python-based pricing libraries for global trading desks.
- Company: Global trading and investment group with a focus on energy and commodities.
- Benefits: Competitive salary, full-time role, and opportunities for professional growth.
- Why this job: Shape advanced pricing analytics that drive trading performance and decision-making.
- Qualifications: Expert in Python with strong knowledge of financial mathematics and derivatives pricing.
- Other info: Join a dynamic team with a focus on innovation and collaboration.
The predicted salary is between 36000 - 60000 £ per year.
This global trading and investment group operates across energy, commodities, and financial markets, combining advanced quantitative methods with large-scale technology infrastructure. Its London engineering hub plays a central role in developing analytics that power front-office trading, pricing, and risk systems across oil, power, gas, and equity products.
The Quant Developer will design, enhance, and maintain Python-based pricing and valuation libraries used across global trading desks. These libraries underpin real-time and end-of-day risk workflows and ensure consistency between valuation, risk, and front-office systems. The role requires a technically skilled developer with a solid grasp of financial mathematics and derivatives pricing, capable of implementing and optimising complex models in a production setting.
Key Responsibilities- Develop and maintain Python pricing and risk libraries covering vanilla and structured options across commodities and equities.
- Implement and calibrate models such as Black–Scholes, Heston, SABR, and Monte Carlo-based approaches for structured instruments (APOs, CSOs, ULDs, P1X).
- Design and maintain volatility surface calibration workflows, including interpolation, extrapolation, and smoothing.
- Collaborate with quantitative researchers and data engineers to translate model specifications into robust, production-grade code.
- Manage market data dependencies, proxy logic, and curve handling for valuation and risk analytics.
- Enhance model performance, numerical stability, and diagnostic visibility.
- Contribute to regression testing, benchmarking, and CI/CD workflows in Python and AWS environments.
- Act as subject-matter expert for pricing models and valuation logic, supporting risk and trading teams globally.
- Expert-level Python developer with strong experience in numerical computing (NumPy, SciPy, Pandas).
- Deep understanding of derivatives pricing theory, volatility modelling, and stochastic calculus.
- Experience with calibration, curve bootstrapping, and risk measures (Greeks, sensitivities, VaR).
- Background in pricing and risk models for commodities or equity derivatives.
- Familiarity with cloud-based compute environments (AWS ECS, Lambda, S3) and DevOps tools (Git, Jenkins, Docker/Kubernetes).
- Knowledge of C++ or C# for potential model integration advantageous.
- Ability to interpret and implement quantitative research efficiently and transparently.
- 5–10 years of experience in quantitative development or model engineering within trading, banking, or commodities.
- Advanced degree (Master’s or PhD) in Mathematics, Physics, Financial Engineering, or a related quantitative field.
- Demonstrated delivery of robust pricing models and scalable production code.
- Strong analytical skills and precision in solving complex numerical problems.
- Excellent communicator, comfortable bridging quantitative, technical, and business perspectives.
This position underpins the evolution of the firm’s global pricing and risk architecture. The Quant Developer ensures model integrity, accuracy, and scalability—contributing directly to trading performance and decision-making. It’s an opportunity to shape how advanced pricing analytics are engineered and deployed across a high-performing global trading business.
RequirementsPython, AWS
Quantitative Developer in London employer: Lithe Consulting Ltd
Contact Detail:
Lithe Consulting Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Developer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a GitHub repo with some cool projects related to quantitative development. It’s a great way to demonstrate your Python prowess and understanding of financial models.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of derivatives pricing and be ready to discuss your past projects. We want to see how you think and solve problems on the spot.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Quantitative Developer in London
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python expertise in your application. We want to see how you've used it in real-world scenarios, especially in numerical computing and model development. Don't hold back on showcasing any projects or libraries you've worked on!
Demonstrate Your Financial Knowledge: Since this role is all about pricing and risk, it's crucial to demonstrate your understanding of derivatives pricing and financial mathematics. We love seeing candidates who can connect their technical skills with financial concepts, so share any relevant experience you have!
Tailor Your Application: Take the time to tailor your application to our job description. We appreciate when candidates align their experiences with the key responsibilities and skills we’re looking for. It shows us that you’ve done your homework and are genuinely interested in the role!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates. Plus, it’s super easy to do!
How to prepare for a job interview at Lithe Consulting Ltd
✨Know Your Python Inside Out
As a Quantitative Developer, you'll be expected to demonstrate expert-level Python skills. Brush up on libraries like NumPy, SciPy, and Pandas, and be ready to discuss how you've used them in past projects. Practising coding challenges related to numerical computing can really help you shine.
✨Master the Financial Mathematics
Make sure you have a solid grasp of derivatives pricing theory and volatility modelling. Be prepared to explain models like Black-Scholes and Heston, and even walk through how you would implement them. This shows not only your technical skills but also your understanding of the financial concepts behind them.
✨Showcase Your Collaboration Skills
Collaboration is key in this role, so think of examples where you've worked with quantitative researchers or data engineers. Highlight how you translated complex model specifications into production-grade code. This will demonstrate your ability to bridge the gap between theory and practical application.
✨Familiarise Yourself with Cloud Environments
Since the role involves working with AWS and DevOps tools, make sure you're comfortable discussing your experience with cloud-based environments. If you’ve used AWS ECS, Lambda, or Docker, be ready to share specific examples of how you’ve leveraged these technologies in your work.
