Location
London

Hours
Full Time

Salary
Negotiable

About the Role
FTSE Russell, part of London Stock Exchange Group (LSEG), is seeking a skilled and motivated Quantitative Engineer to build robust, scalable and automated applications supporting trillions in assets. This role sits at the intersection of finance and technology, requiring a combined understanding of software engineering, quantitative finance and data analysis to develop the next generation of Index solutions. You will work alongside analysts and engineers to deliver high-quality software, fostering a culture of learning, innovation and continuous improvement.

Key responsibilities include writing clean, efficient and maintainable code to support index calculations, back-testing, performance attribution and analytics frameworks. You will build tools to streamline index monitoring, validation and rebalancing, integrate and analyze diverse financial datasets, and implement RESTful APIs, cloud-native solutions and automated CI/CD pipelines. The role also involves collaborating with Product, Research and Operations teams to support their activities and extend the firm’s analytics and product offerings.

This is an excellent opportunity to gain in-depth exposure to quantitative methods, systematic investment strategies and the full lifecycle of FTSE Russell’s product offering while working in a dynamic, inclusive and innovative environment.

Experience
Minimum 2 years of quantitative analytics, research and development experience within financial services, such as a bank, asset manager, insurance company or related vendor. Strong expertise in risk management, portfolio construction, systematic investment strategies, and cross-asset cash and derivative instruments is required.

About you
You are detail-oriented with excellent problem-solving skills and the ability to think laterally to solve business problems. You can work effectively under tight deadlines, learn quickly and communicate complex information clearly and concisely. You embrace teamwork, innovation and continuous improvement.

Qualifications
Graduate with an advanced degree (MSc or PhD) in Mathematics, Computer Science, Financial Engineering, Statistics, Physics or a related scientific discipline. Additional professional qualifications are welcome.

Strong programming skills in Python and SQL, with experience in data analytics libraries such as numpy, pandas, scipy and cvxpy. Familiarity with stored procedures, code version control tools like GIT, and API implementation is expected.

Solid background in software engineering best practices, including writing high-performance code, data structures, algorithm development and code optimization. Additional programming skills in C# or Java, and experience with JSON and XML configuration management are advantageous.

Database experience with SQL Server, Sybase, Snowflake or PostgreSQL, and cloud development skills using AWS services (EC2, Lambda, Glue, EKS, SQS) or similar platforms are highly desirable.