Job Duties: Vice President, Quantitative Engineering with Goldman Sachs & Co. LLC in West Palm Beach, FL. Lead the research, development, and productionization of the alpha strategy for Credit products, encompassing a wide range of technical and fundamental signals. Analyze large data sets (structured and unstructured) to build predictive models of business-relevant market variables, leveraging statistical tools as well as machine learning and AI methods. Conceptualize, build, and deploy robust, large-scale quoting systems with a high degree of scalability and adaptability to changing market conditions. Collaborate with internal stakeholders, engineers, and traders; take a leading role in coordinating projects, gathering ideas, and identifying strategic needs. Determine how requirements fit into massive, existing infrastructure and software to minimize additional complexity. Develop quantitative models suiting the needs of a market-making algorithm and tailored to the particularities, challenges and opportunity set of current corporate bond markets. Mentor, guide, and assist in development of staff, including Analyst and Associate team members.
Job Requirements: Master’s degree (U.S. or foreign equivalent) in Mathematics, Computer Science, Financial Engineering, Applied Mathematics, or related quantitative field and three (3) years of experience in job offered or a related quantitative engineering role OR Bachelor’s degree (U.S. or foreign equivalent) in Mathematics, Computer Science, Financial Engineering, Applied Mathematics, or related quantitative field and five (5) years of experience in job offered or a related quantitative engineering role. Prior experience must include three (3) years of experience (with a Master’s degree) OR five (5) years of experience (with a Bachelor’s degree) with: performing financial mathematics, including at least one of the following: stochastic calculus, no-arbitrage pricing theory, multivariable calculus, linear algebra, probability theory, numerical methods, or Monte-Carlo techniques; performing analysis leveraging market risk, credit risk, liquidity risk, or mathematical finance concepts; object-oriented programming and scripting programming languages such as Python or Java; implementing mathematical models or analytics in production-quality software; working with database query languages, such as SQL, MongoDB, or other data management tools to process large datasets; and applying algorithms or data structures to write complex programs. Prior experience must include two (2) years of experience with: C++, Java, or Python; developing pricing models for financial products to model risk, economics, and cash flows under normal and distressed market environments.