VP, Quantitative Engineering — Risk Modeling & Data Science

Goldman Sachs Group, Inc.; Salt Lake City (UT); On-site; USD 200,000 - 320,000; Full time

Job summary

Goldman Sachs Group, Inc. in Salt Lake City, Utah seeks a Vice President of Quantitative Engineering to lead scenario development across economic and financial variables.

You will collaborate with stakeholders, analyze user needs from a scenario design perspective, and address data, model, and implementation issues. Responsibilities include building predictive models from large structured and unstructured data, refining risk models across market, credit, and liquidity risk, and maintaining

Qualifications

• Master's degree or higher in Mathematics, CS, Financial Engineering or related field with relevant experience.
• Experience in building predictive models and risk analytics.
• Strong programming skills in C++, Python, and Java; production-grade software development.

Responsibilities

• Lead development and documentation of scenarios across economic and financial variables.
• Analyze large data sets to build predictive models for market variables.
• Develop, refine, and improve risk models and document testing approaches.

Skills

C++

Python

Java

Stochastic calculus

Numerical methods

Monte-Carlo techniques

Data analysis

OO programming

Education

Master's degree in a quantitative field

Bachelor's degree in a quantitative field

PhD in a related field

Tools

SQL

MongoDB

Git

Job description

Goldman Sachs Group, Inc. in Salt Lake City, Utah seeks a Vice President of Quantitative Engineering to lead scenario development across economic and financial variables.

You will collaborate with stakeholders, analyze user needs from a scenario design perspective, and address data, model, and implementation issues. Responsibilities include building predictive models from large structured and unstructured data, refining risk models across market, credit, and liquidity risk, and maintaining