Lead Quantitative Analyst - QRM
Summary
Reporting to the VP in Quantitative Risk Management (QRM), the lead analyst will work closely with the other quantitative analysts, business users and IT colleagues to develop and implement models for pricing and setting margin requirements of complex financial derivatives, as well as support and enhance existing systems in that domain.
Essential Duties and Responsibilities:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.
- Lead development of pricing and risk analytic models and tools to support risk management
- Develop high-performance numerical algorithms, conforming to the high reliability and availability standards of the organization
- Lead projects and coordinate deliverables in collaboration with other departments, including FRM, CCRA, Model Validation
- Review models and algorithms of other team members
- Serve as a point of contact and a subject matter expert for other departments
- Write and review documentation, including executive summaries for business users and management
- Implement algorithms in R, Python, Matlab, Java or other relevant software language.
- Work collaboratively with other members of FRM, as well as MVG/AD/QA for the review and implementation of models.
Supervisory Responsibilities:
- None
Qualifications:
The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Graduate degree in a quantitative field such as financial engineering, quantitative finance, statistics, physics, mathematics, computer science, economics
- Strong knowledge of financial derivatives in general.
- Strong knowledge in equity derivative pricing models and volatility modeling.
- Strong quantitative skills in derivatives valuation, risk factor identification, risk modeling, scenario analysis and stress testing.
- In-depth knowledge of statistical methods and data mining techniques.
- Preference given to candidates with strong knowledge in asset classes like equities, interest rates, volatility, commodities, and foreign currencies.
- Excellent oral and written communication skills
- Strong problem-solving skills
- 5-10 years of financial industry experience is preferable
Technical Skills:
- Broad knowledge across: financial modeling (pricing and simulation), financial econometrics, derivative instruments across asset classes, numerical methods, mathematical programming, risk management, stress testing, with specialist expertise in several of these areas.
- Expert level proficiency in a quantitative scripting language such as R, Python, Matlab
- Experience with one or more statistical and econometric packages
- Development experience in Java or similar language is desirable
Education and/or Experience:
- Master’s degree or higher (preferably PhD) in Finance, Economics or a quantitative field such as Physics or Mathematics
Certificates or Licenses:
- None required
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