Analyze and model the risk characteristics of derivatives products including forwards, futures, swaps, and options across asset classes
Perform daily validation of risk analytics across the liquid alternatives set of portfolios.
Monitor key risk metrics, including greeks, factor exposures, systematic and idiosyncratic risk, performance attribution, stress testing and Value at Risk (VaR).
Conduct root cause analysis on any discrepancies in portfolio and security risk analytics, investigating potential issues related to instrument data quality, security master setup, holdings, and modeling of thinly traded securities.
Play a key role in onboarding new liquid alternative strategies onto the risk platform.
Design and implement the business logic and codebase that fills instrument templates with complete terms and conditions needed for the security pricing engine.
Collaborate with technology teams to create and validate instrument loaders and data export pipelines.
Contribute to the design of the internal data architecture for storing analytics and establishing robust data quality processes.
Work with risk managers to develop new risk reports and analytics that enhance transparency and understanding of strategy risks.
Requirements
5+ years investment industry experience, preferably in a quantitative investment role or portfolio analytics function within an investment management company
Master's degree in a quantitative field such as Financial Engineering, Computational Finance, Financial Mathematics, Statistics, or a related discipline
CFA or FRM is strongly desired.
Strong understanding of risk analytics of derivatives products across multiple asset types including commodities, FX, equities, credit, and rates.
Proven experience in a quantitative risk management or analytics role within the financial industry, leveraging statistical modeling, programming and large-scale data management.
Proficiency in SQL and Python for data analysis and scripting.
Ability to re-write and debug fundamental python libraries is a strong plus.
Hands-on experience with risk systems such as RiskMetrics and Barra is highly desirable.
Experience with data visualization tools like Tableau, python-dash, or python-Streamlit is a plus.
Excellent analytical and problem-solving skills with a high level of attention to detail.
Strong written and verbal communication skills, with the ability to explain complex quantitative concepts to a non-technical audience.
A proactive and results-oriented mindset with the ability to manage multiple tasks and projects effectively in a fast-paced environment.
Knowledge of bond and equity markets, alternatives, pricing and performance attribution data.
Tech Stack
Python
SQL
Tableau
Benefits
comprehensive health care coverage and emotional well-being support
market-leading retirement
generous paid time off and parental leave
charitable giving employee match program
educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career