Vice President, GBM - Public, ETF Trading

Goldman Sachs

Confirmed live today High trust

Quick summary

Work type: On-site
Location: New York, NY
Salary: $150,000–$300,000 / yr
Posted: 103 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $188k

This role $225k

$123k $319k

below market most similar roles pay here above market

This role pays more than 81% of similar roles. Most pay $154,500–$220,900 — the blue band above. At the midpoint, this role pays about $225k 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 71 open roles on FindRole.

Listed pay typically runs $140,000–$250,000 across 34 roles with salary data.

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At a glance

TL;DR · Vice President, GBM - Public, ETF Trading

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The GBM - Public, ETF Trading, Vice President - New York role involves joining a dynamic trading team as a Systematic ETF Trader. The successful candidate will design, develop, and implement algorithmic trading strategies for ETFs across global markets. Daily responsibilities include utilizing historical and real-time market data to create predictive models, conducting rigorous backtesting to optimize risk-adjusted returns, and managing automated trade execution to minimize slippage and transaction costs. The position requires monitoring market, liquidity, and operational risks while collaborating with quantitative researchers and data scientists. Key technical requirements include proficiency in Python, C++, Java, SQL, and MATLAB. Candidates must apply skills in statistics, econometrics, and machine learning to solve problems related to ETF structure, liquidity, and market microstructure within a systematic trading framework.

Skills

Python C++ Java SQL MATLAB Algorithmic Trading Backtesting Financial Modeling Data Analysis Machine Learning Statistics Econometrics ETFs Risk Management

What you'll do

Design, develop, and implement algorithmic trading strategies for ETFs across global markets.
Analyze historical and real-time market data to create predictive models for trading decisions.
Conduct rigorous backtesting of trading strategies to optimize for risk-adjusted returns.
Manage and execute trades through automated systems while minimizing slippage and transaction costs.
Monitor and manage market, liquidity, and operational risks to ensure compliance with guidelines.
Track and analyze strategy performance to implement iterative changes that enhance profitability.
Use advanced tools like Python, SQL, and MATLAB for data analysis and strategy development.

What we're looking for

Bachelor's degree in Finance, Economics, Engineering, Computer Science, Mathematics, or a related field.
At least 2 years of experience as a quantitative trader, systematic trader, or similar role.
Proven experience with ETFs and algorithmic trading.
Proficiency in programming languages such as Python, C++, or Java.
Experience in financial modeling, data analysis, and backtesting.
Strong background in statistics, econometrics, or machine learning techniques.
Deep understanding of financial markets, including ETF structure, liquidity, and market microstructure.
Strong verbal and written communication skills for cross-team collaboration and stakeholder presentations.

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