Quantitative Data Developer

TS Imagine; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Vacation and Personal days

Annual bonus and salary review

Training Budget $1,500

Health, dental, life assurance, and ey

care vouchers

Pension scheme

Job summary

TS Imagine, a global leader in trading and risk management, seeks a Quantitative Data Developer for our London office. Design and maintain data solutions for valuing positions and constructing quantitative datasets used in market risk calculations across asset classes.

You will collaborate with Quant Developers on major projects, building high-performance data applications with Python, SQL, and Snowflake, and document methodologies to enable robust validation and transparent analytics.

Qualifications

• M.S. or PhD in mathematics, physical sciences, or engineering preferred.
• 3–5 years of large-scale Python development and data-intensive product experience.
• Experience with financial derivatives and market conventions is essential.
• Live/intraday data experience for curves, volatility surfaces, and risk tools is a plus.

Responsibilities

• Collaborate with Quant Developers on major projects to optimize data pipelines and analytics infrastructure for performance and reliability.
• Design and develop robust data solutions to process inputs for pricing models and market risk calculations across asset classes.
• Develop high-performance, scalable data applications using Python, SQL and Snowflake to analyze large-scale financial datasets.
• Document data methodologies to support internal and external validation processes.

Skills

Python development

SQL programming

C++

Java

Quantitative finance knowledge

Education

M.S. or PhD in mathematics, physical sciences, or engineering

Tools

Snowflake

Job description

TS Imagine, a global leader in trading and risk management SaaS-based software, is seeking a Quantitative Data Developer to join our Models and Quantitative Data team in our London office!

As a Quantitative Data Developer, you will play a pivotal role in discovering, designing, developing, and maintaining data solutions that support the valuation of financial positions and the construction of quantitative datasets (e.g., curves, volatility cubes, correlation matrices). You will also contribute to the development of robust data-driven systems for market risk calculations (e.g., VaR, greeks) in real-time across all asset classes. Our cutting-edge risk and data solutions are trusted by some of the world’s most prestigious financial institutions, including global investment banks and multi-strategy hedge funds.

Who will love this job

• A scientist – you are comfortable with numerical methods, linear algebra, partial differential equations, probability theory and statistics
• An engineer – who has a passion for computer science, system performance, clean code and architecture with an owner mentality
• A data enthusiast – You enjoy working with large datasets, transforming raw data into meaningful inputs, and solving complex problems with a methodical approach
• A doer – who is enthusiastic about new challenges, accepts a broad spectrum of responsibilities, and works hard to produce a high-quality result
• A learner – who is not afraid of being outside the comfort zone and is ready to dive into some of the most complicated problems in finance
• An excellent teammate – who has a combination of technical and personal qualities to thrive in a cutting-edge software development environment

What you’ll do

• Collaborate with Quant Developers on major projects to optimize data pipelines and analytics infrastructure for maximum performance and reliability.
• Design and develop robust data solutions to efficiently process and deliver inputs for pricing models and market risk calculations across various asset classes, including equity, credit, FX, fixed income, commodities, crypto, and their derivatives.
• Develop and manage high-performance, scalable data applications and tools using Python, SQL, and Snowflake to analyze, transform, and ensure the accuracy of large-scale financial datasets for efficient model input construction.
• Document data methodologies comprehensively to provide transparency and support for both internal and external validation processes.

What you should have

• M.S. or PhD in mathematics, physical sciences, or engineering preferred
• Demonstrated expertise in quantitative and programming skills, with 3–5 years of experience in large-scale Python development, SQL programming, and working on data-intensive products.
• Experience with other programming languages (C++, Java)
• Understanding of financial derivatives, market conventions and their implementation is a must
• Proficiency with financial data structures like yield curves (OIS, Libor, cross-currency), inflation curves, volatility surfaces, and interest rate volatility cubes (live/intraday data experience preferred)
• Experience in developing risk management tools such as VaR, Monte Carlo, scenario analysis and P&L is preferred

Why TS Imagine / Benefits

• Please note: This role requires applicants to be based in London, as it is anin-officeposition.Remote work is not possible.
• Vacation and Personal days
• Annual bonus and salary review
• Training Budget $1,500
• Health, dental, life assurance, and eye care vouchers
• Salary sacrifice pension scheme

About TS Imagine

Created out of the combination of two best-in-class SaaS platforms, TradingScreen and Imagine Software, TS Imagine delivers integrated trading, portfolio and real-time risk solutions for capital markets. The platform is uniquely positioned to streamline complex and time-consuming workflows across front, middle, and back office functions. TS Imagine has close to 400 employees in 10 offices worldwide, serving approximately 500 global buy‑side and sell‑side institutions across North and South America, EMEA, and Asia Pacific including hedge funds, traditional asset managers, pension funds, mutual funds, and financial institutions.

We challenge our employees every day to think creatively and innovate across silos and across platforms.