Vice President, Market Risk Strats

Goldman Sachs

Quick summary

Work type: On-site
Location: New York, NY
Salary: $130,000–$250,000 / yr
Posted: 1 day ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $188k

This role $190k

$116k most similar roles pay here $264k

This role pays more than 59% of similar roles. Most pay $156,954–$219,287 — the shaded band above. At the midpoint, this role pays about $190k versus about $188k for comparable roles.

Based on 240 similar postings.

Employer

About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 187 open roles on FindRole.

Listed pay typically runs $130,000–$250,000 across 60 roles with salary data.

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At a glance

TL;DR · Vice President, Market Risk Strats

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Join the Risk Strats team as a senior quantitative expert responsible for driving efficient risk management across market, credit, liquidity, and capital exposures. You will design and implement advanced models and metrics using optimization, stochastic calculus, and machine learning to assess risks and support regulatory compliance. Day-to-day tasks include developing large-scale risk infrastructures with languages like Python or Java, leveraging Large Language Models (LLMs) for automated analysis and explanation, and iterating based on stakeholder feedback. Ideal candidates have a strong background in mathematics, physics, or engineering, experience with LLMs over financial data, and the ability to balance technical rigor with commercial pragmatism.

Skills

Python Java C++ LLMs RAG Scala CI/CD PostgreSQL MongoDB Kafka Docker AWS Azure Git Jenkins Prometheus Grafana

What you'll do

Develop and maintain quantitative risk models using advanced mathematical approaches.
Perform detailed analysis on risk trends and communicate insights to stakeholders.
Design and implement large-scale risk infrastructure systems for efficiency.
Build LLM agents over financial data to automate analysis and explanation.
Update risk models based on business growth and changing risk environments.

What we're looking for

Postgraduate degree in mathematics, physics, electrical engineering or related field.
Hands-on experience building LLM agents over financial data to automate analysis and explanation.
Strong commercial mindset with proven ability to deliver pragmatic solutions quickly.
Expertise in developing risk models using advanced mathematical/statistical/engineering approaches.
Experience designing highly scalable, efficient, robust systems for risk management.

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