VP, Quantitative Engineering & AI Modeling

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

Job summary

Goldman Sachs Services LLC in New York, NY seeks a Vice President, Quantitative Engineering to lead design, development, and deployment of advanced quantitative models and scenarios for time series forecasting, incorporating economic and business-risk variables.

You will drive end-to-end model development, validation, and documentation for Model Risk Management, build explainable ML models for event prediction, and collaborate with risk and finance teams across the firm.

Qualifications

• PhD or Master's or Bachelor's in a quantitative field with related experience.
• Programming languages include C++, R, Python; econometrics and time-series analysis; Monte Carlo simulation and conformal prediction; production cloud deployment; data management; model validation and documentation; AI agent development.

Responsibilities

• Lead design and implementation of advanced quantitative models and scenarios for time series forecasting.
• Develop and deploy explainable ML models for event prediction and risk scoring.
• Conduct end-to-end model development lifecycle from data collection to cloud deployment.
• Create and maintain technical documentation for Model Risk Management reviews.

Skills

C++

R

Python

Time-series analysis

Econometrics

Uncertainty quantification

Explainable ML

Cloud deployment

Data management

Model validation

AI agent development

Education

PhD in Mathematics/CS/Financial Engineering/Applied Mathematics or Statistics

Master's in Mathematics/CS/Financial Engineering/Applied Mathematics or Statistics

Bachelor's in Mathematics/CS/Financial Engineering/Applied Mathematics or Statistics

Job description

Goldman Sachs Services LLC in New York, NY seeks a Vice President, Quantitative Engineering to lead design, development, and deployment of advanced quantitative models and scenarios for time series forecasting, incorporating economic and business-risk variables.

You will drive end-to-end model development, validation, and documentation for Model Risk Management, build explainable ML models for event prediction, and collaborate with risk and finance teams across the firm.