VP, Quantitative Engineering & AI Risk Modeling

Goldman Sachs Bank AG; New York (NY); On-site; USD 191,000 - 237,000; Full time

Benefits offered by this job

Health insurance

Vacation policy

Education assistance

Job summary

Goldman Sachs Services LLC in New York, NY seeks a Vice President of Quantitative Engineering to lead end-to-end model development for time-series forecasting, including data collection, feature engineering, model selection, and scalable cloud deployment.

The role emphasizes uncertainty quantification, explainable ML, and collaboration across Finance and Risk departments, with rigorous validation and documentation. Strong programming and ML skills required.

Qualifications

• PhD or Master’s with years of experience in quantitative engineering roles.
• Proficiency in C++, R, Python and modern time-series techniques.
• Experience with production cloud deployment and data management at scale.

Responsibilities

• Lead design, development, and deployment of advanced quantitative models.
• Conduct uncertainty quantification and explainable ML for event prediction and risk scoring.
• Create comprehensive model risk documentation and governance reports.

Skills

C++

Python

R

Time-Series Analysis

Machine Learning

Explainable ML

Education

PhD in Mathematics/CS/Financial Engineering/Applied Mathematics

MS in Mathematics/CS/Financial Engineering/Applied Mathematics

Bachelor’s in Mathematics/CS/Financial Engineering/Statistics

Tools

Cloud deployment

Data management

Simulation techniques

Conformal Prediction

Job description

Goldman Sachs Services LLC in New York, NY seeks a Vice President of Quantitative Engineering to lead end-to-end model development for time-series forecasting, including data collection, feature engineering, model selection, and scalable cloud deployment.

The role emphasizes uncertainty quantification, explainable ML, and collaboration across Finance and Risk departments, with rigorous validation and documentation. Strong programming and ML skills required.