Vice President, Quantitative Engineering

Goldman Sachs

Quick summary

Work type
On-site
Location
New York, NY
Salary
$74,000–$276,000 / yr
Posted
1 day ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $188k
This role $175k
$50k most similar roles pay here $300k

This role pays less than 62% of similar roles. Most pay $150,350–$225,000 — the shaded band above. At the midpoint, this role pays about $175k 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, Quantitative Engineering

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As a Vice President in the Quantitative Engineering team within Global Banking & Markets at Goldman Sachs in New York, you will lead the development and implementation of complex financial scenarios using economic and financial variables. Your daily tasks include building and improving electronic trading systems for interest rate products, implementing data-driven algorithms with statistical models to identify revenue opportunities, and communicating with trading and sales teams on both short-term requests and long-term strategic initiatives. You will mentor junior team members while leveraging C++, Java, or Python to develop automated quoting, risk management, and execution algorithms. The role requires expertise in quantitative analysis using advanced econometric techniques such as Bayesian analysis and machine learning, along with experience in developing scalable data management tools for risk oversight.

Skills

Python C++ Java Bayesian analysis Time series analysis Machine learning algorithms Linear Regression Data management tools Risk management Scenario-based analysis Statistics Performance analysis Econometric techniques

What you'll do

  • Lead development and implementation of economic and financial scenarios for firm businesses.
  • Develop and maintain electronic trading systems for hedging interest rate products.
  • Implement data-driven algorithms using statistical models to identify revenue opportunities.
  • Build and improve electronic trading algorithms based on historical quantitative data.
  • Communicate daily issues, feature requests, and strategic direction with trading and sales teams.

What we're looking for

  • Bachelor’s degree in Mathematics, Computer Science, Financial Engineering, Applied Mathematics, or related quantitative field.
  • 4 years of experience developing automated trading and risk management algorithms using C++, Java, or Python.
  • Expertise in quantitative analysis with advanced econometric, statistical, and mathematical techniques like Bayesian analysis and machine learning.
  • Experience in performing risk management and scenario-based analysis for financial products.
  • Proficient in building data-driven performance analysis tools using Linear Regression and Time Series Analysis.
  • Strong communication skills to interact with trading and sales teams on daily issues and strategic initiatives.
  • Mentorship experience guiding junior and mid-level team members in quantitative engineering.

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