Analyst, Quantitative Research

Job Description

Job Purpose

The selected candidate will join the Global Quantitative Research team at ICE which designs, implements, and supports enterprise quantitative models and systems. The primary responsibility of this position will be to lead quantitative research and implementation team supporting various business functions at ICE (Exchange, Data Services, etc.). This job requires strong quantitative finance skills, a passion to see projects succeed and a strong attention to detail. It requires programming skills as well as mathematical knowledge. This role will interact with various teams of different backgrounds and expertise, so the ability to communicate clearly and concisely is a must. This role will have direct exposure to interest rate derivatives, equity derivatives, credit derivatives and commodity derivatives. Knowledge of Clearing operations and a strong background in derivatives pricing and theory is preferred.

Responsibilities

• Drive clearing house margin, stress and collateral management models R&D.
• Define business requirements and specifications for model upgrades and enhancements.
• Perform risk analysis and develop risk solutions for new products across all asset classes.
• Model specific risks such as concentration charges and wrong way risk.
• Contribute strongly to “hands-on” and ad-hoc requests for development and solutions in time-critical situations.
• Document and present risk models and risk reports for clearing members, regulators, risk committees and boards.
• Interact with risk departments to provide support for existing clearing house quantitative models.
• Interact with technology groups for production implementation design.
• Candidate will be working the US shift initially. However, this can evolve as the team matures and candidate should be flexible to work any shift as per business requirements.
  
  

Knowledge And Experience

• PhD or Masters in Physics, Mathematics, Quantitative Finance, Statistics, or a relevant scientific field.
• 2+ years of work experience in quantitative finance fields from financial institutions, with proven record designing or implementing quantitative finance models.
• Strong mathematical knowledge of financial derivatives pricing and risk management models.
• Excellent quantitative, analytical and problem-solving skills with solid knowledge of statistics, particularly time series analysis.
• Excellent C++ and Python required, and 2+ years of experience preferred.
• Strong numerical methods skills.
• Capable of working under pressure within a diverse team to accommodate tight deadlines.
• Excellent oral and written communication skills.