Analyst, Quantitative Research

Key Skills

Analytical and Problem solving, Big Data Technology, C Programming, C++, Deep Learning, Effective communication skills, Machine learning techniques, Python Programming, SciPy, SQL

Job Description

The incumbent will work as part of the ICE global quantitative research team to provide risk model analytics and quantitative risk management solutions to the 1st line Clearing Risk Department as well as other business lines in ICE. The role will be working on different financial derivatives across various assets classes from equities, commodities, fixed income to credit default swaps (CDS). The successful candidate will engage with various groups in the organization from product control to front line risk teams and sales teams.

Responsibilities

• Research, develop and Implement risk management models for the Clearing Business
• Work with risk managers to provide quantitative supports and analytical tools to investigate and understand markets risks, liquidity risks, counterpart credit risks, etc.
• Model review, documentation and validation remediation to ensure compliance with the Model Risk Governance Framework (MRGF)
• Review and interpret results of on-going model performance tests (e.g. back testing)
• Develop and implement new quantitative models and pricing functions
• Contribute to the quant code maintained by the global Quant group
• Work and coordinate with model validators in model validation/re-validation review process
• Prepare analyses for regulatory submissions of model changes and introduction of new models.

Knowledge and Experience

• MSc in Physics, Mathematics, Quantitative Finance, Statistics, or a relevant scientific field or relevant work experience
• Strong mathematical knowledge of financial derivatives pricing and risk management models
• Good data science experience
• Strong C++ or Python programing skills
• Experience with SQL
• Solid numerical programming abilities
• Excellent attention to detail with ability to work independently and also as part of a team
• Excellent problem solving, critical thinking, and communication skills
• Excellent command of written and spoken English.

Preferred

• PhD in mathematics, physics, computer science or a related field.
• Experience writing large models in Python utilizing numpy, scipy, scikit-learn and related numerical libraries.
• Experience with numerical techniques (Optimization, root finding..etc).
• Experience with C++
• Previous experience in the financial services field, with emphasis on Market Risk area.

Schedule

This role offers work from home flexibility of up to 2 days per week.