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Quantitative Strategist, Global Banking & Markets, Global Currency and Emerging Markets; GCEM

Job in New York, New York County, New York, 10261, USA
Listing for: The Goldman Sachs Group
Part Time position
Listed on 2026-01-15
Job specializations:
  • Finance & Banking
    Financial Consultant, Data Scientist, Financial Analyst
Salary/Wage Range or Industry Benchmark: 150000 USD Yearly USD 150000.00 YEAR
Job Description & How to Apply Below
Position: Quantitative Strategist, Global Banking & Markets, Global Currency and Emerging Markets (GCEM)
Location: New York

What We Do

At Goldman Sachs, quantitative strategists are the cutting edge of our businesses, solving real‑world problems through a variety of analytical methods. Working in close collaboration with traders and sales, the strats' invaluable quantitative perspectives on complex financial and technical challenges power our business decisions.

Within our Global Banking & Markets business, our Global Currency and Emerging Markets (GCEM) team works closely with our trading desks to develop quantitative and technological techniques to solve complex business problems. Desk strats sit on trading floors and provide value for both internal and external clients through cutting‑edge models, predictive analytics, and high‑quality trading tools. We are a dynamic, entrepreneurial team with a passion for the markets, with individuals who thrive in fast‑paced, changing environments and are energized by a bustling trading floor.

Who

We Look For

We're looking for candidates with strong quantitative, programming, and communication skills with a keen interest in applying those skills in the financial markets. As a desk strat on our GCEM trading desk, you’ll have the opportunity to apply your quantitative acumen toward solving complex problems and creating innovative solutions for our clients.

Your work will directly impact the firm’s bottom line. Whether it’s developing automatic pricing algorithms to help our trading desks make better decisions or building a pricing model product that will help clients hedge risk, you’ll create an immediate commercial impact for the firm.

Given our GCEM desk is a global cross‑asset desk, you’ll also gain exposure to a wide range of asset classes & risk factors (Credit, FX, Rates, vanillas, options, structured exotics). This role will be an invaluable opportunity to sharpen your skills in different domains and build a deep & broad foundation of product knowledge.

Responsibilities

Within this role, you’ll create value by providing effective Luís& efficient Ribeiro solutions to our GCEM trading desk, in one or multiple asset classes including Rates, FX, and Credit, from One Delta to Exotics products.

This includes but is not limited to:

  • Conducting research and deploying machine learning models for trading.
  • Developing and optimizing market‑making algorithms and systems.
  • Pricing and hedging analysis for complex transactions.
  • Developing and maintaining cutting‑edge derivative pricing models.
Qualifications
  • Advanced degree, preferably PhD, in a quantitative field such as Mathematics, Computer Science, Machine Learning, Physics, etc.
  • Deep knowledge of cutting‑edge machine Trekning models.
  • Self‑driven, quick learner, can‑do attitude, results‑oriented.
  • Excellent written and verbal communication skills.
  • Strong problem‑solving and analytical skills.
  • Strong coding skills.
  • 1-5 years of relevant experience is preferred.
Salary Range

The expected base salary for this New York, New York, United States‑based position is $150,000‑$225,000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year‑end.

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Benefits

Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non‑temporary, full‑time and part‑time US employees who work at least 20 hours per week, can be found here.

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