At a Glance
- Tasks: Develop and support quantitative models and risk analytics for clearing houses.
- Company: Join a leading financial institution at the forefront of quantitative finance.
- Benefits: Competitive salary, professional development, and opportunities to work with cutting-edge technology.
- Other info: Collaborative culture with opportunities for innovative research and career growth.
- Why this job: Shape risk management and make an impact in a high-performance environment.
- Qualifications: Advanced degree in a quantitative field and strong programming skills in Python and SQL.
The predicted salary is between 63000 - 77000 £ per year.
In this role, you will develop and support enterprise quantitative models and risk analytics for clearing houses, blending quantitative research with data science. You will build scalable data pipelines and production-ready software to enable model implementation and risk assessment across asset classes. You’ll collaborate with Risk, Technology, and senior stakeholders to advance data-driven solutions and innovative quantitative finance research, shaping risk management in a demanding, high-performance environment.
Responsibilities
- Lead research and development of margin, stress testing, and risk management models for clearing houses.
- Perform quantitative risk analysis across asset classes (rates, equities, credit, commodities).
- Conduct data exploration, statistical analysis, and time series modeling for research.
- Build production-quality, data-driven software for model implementation and analytics.
- Develop ETL pipelines and data management tools for large-scale datasets.
- Diagnose data issues and advise on data architecture and governance.
- Define business requirements for model enhancements and data workflows.
- Develop and maintain in-house quantitative research platforms and analytics tools.
- Document methodologies and present findings to regulators, risk committees, and senior management.
- Collaborate with technology teams for production integration of models and data systems.
- Engage in innovative research in quantitative finance and data science.
Key requirements
- Advanced degree (MSc or PhD) in a quantitative field.
- Experience in quantitative finance or data science in financial institutions with a track record in model development or implementation.
- Strong programming skills in Python and SQL; familiarity with R, MATLAB, C++, or Java preferred.
- Working knowledge of relational databases (Oracle, Postgres, Snowflake) and Git.
- Solid understanding of statistics, time series analysis, and derivatives pricing and risk management.
- Ability to work under pressure in a high-performance environment with tight deadlines.
- Excellent analytical, organizational, and communication skills; capable of articulating complex concepts to diverse audiences.
- Customer-focused, results-oriented, and highly detail-oriented.
Analyst, Global Quantitative Research in London employer: Intercontinental Exchange
Intercontinental Exchange, Inc. (ICE) is an exceptional employer that offers engineers the chance to work on innovative technology within a dynamic and collaborative environment. With a strong focus on employee growth, ICE provides extensive training opportunities and encourages professional development, ensuring that team members can thrive in their careers while contributing to one of the largest global financial networks. Located in a vibrant area, employees enjoy a supportive work culture that values problem-solving and teamwork, making it a rewarding place to build a meaningful career.
