Intercontinental Exchange Holdings, Inc.
Analyst, Global Quantitative Research

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Job Description
Job Purpose
The Quantitative Analyst will join the Global Quantitative Research Group, which designs, implements, and supports enterprise quantitative models and systems. This role blends quantitative research and data science, focusing on model development, risk analytics, and large-scale data engineering. The primary responsibility is to drive quantitative model initiatives for clearing houses while supporting data-driven solutions across multiple business lines. The candidate must demonstrate strong quantitative and programming skills, deep understanding of financial derivatives, and the ability to manage complex data workflows. Frequent interaction with Risk Management, Technology, and Senior Management is expected.
Responsibilities
- Lead research and development of margin, stress testing, and risk management models for clearing houses.
- Perform quantitative risk analysis and develop solutions across multiple asset classes (interest rate, equity, credit, and commodity derivatives).
- Conduct data exploration, statistical analysis, and time series modeling to support quantitative research.
- Build production-quality, data-driven software solutions for model implementation and analytics.
- Develop ETL pipelines and data management tools to ensure reliability, efficiency, and quality of large-scale financial datasets.
- Diagnose and resolve data issues; recommend improvements to data architecture and governance.
- Define business requirements and specifications for model enhancements and data workflows.
- Develop and maintain in-house quantitative research platforms and analytics tools.
- Document and present methodologies, findings, and risk models to stakeholders including regulators, risk committees, and senior management.
- Collaborate with technology teams for production implementation and integration of models and data systems.
- Engage in innovative research in quantitative finance, advanced statistical techniques, and data science.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Knowledge and Experience


Get help with your application
Your very own career expert that helps elevate your application to the next level.
- Advanced degree (MSc or PhD) in Mathematics, Statistics, Physics, Quantitative Finance, Data Science, or a related field.
- Experience in quantitative finance or data science within financial institutions preferred, with proven record in model development or implementation.
- Strong programming skills in Python and SQL; experience with R, MATLAB, C++ or Java preferred.
- Working knowledge of relational databases (Oracle, Postgres, Snowflake) and version control tools (Git).
- Solid understanding of statistics, time series analysis, and financial 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.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location