Execution Quantitative Researcher at Goldman Sachs — BranchFactor

BranchFactor Summary

The original posting with the fluff stripped out

Expected experience: 3–10 yrs
Management level: Individual contributor

Compensation

Base salary	US$125,000 – US$250,000 / yr

Role speciality

Trading & Market Strategies Transaction Cost Analysis (TCA)

Useful technologies

KDB+ Python Q

Preferred qualifications

Field of studyFinancial Engineering, Computer Science, Mathematics, Physics, Statistics (or related)

Study levelMaster's or higher

Original posting

Asset & Wealth Management

A career with Goldman Sachs Asset & Wealth Management is an opportunity to help clients across the globe realize their potential, while you discover your own. As part of one of the world's leading asset managers with over $3 trillion in assets under supervision, you can expect to participate in exciting investment opportunities while collaborating with talented colleagues from all asset classes and regions. Working in a culture that values integrity and transparency, you will join a diverse team that is passionate about our craft, our clients, and building sustainable success. Bringing together traditional and alternative investments, Goldman Sachs Asset & Wealth Management provides clients around the world with dedicated partnership and a focus on long-term performance. As a primary investment area within Goldman Sachs, we provide investment and advisory services for pension plans, sovereign wealth funds, insurance companies, endowments, foundations, financial advisors and individuals.

Central Trading and Market Strategies

The Central Trading and Market Strategies desk is a high-impact team responsible for the trading of Equities, ETF, Futures, and Options portfolios globally for the Quantitative Investment Strategies (QIS) and Fundamental Equities investment funds. We sit at the intersection of technology and investment management, leveraging data-driven insights to optimize trade execution performance. Given the scale and high volume of our global trading activity, execution quality and market impact are critical to fund performance and to how the funds operate overall**.** We are seeking a trading quant to join our systematic trading research team. This role focuses on the rigorous analysis of trading performance, supporting our systematic trading processes, and providing research and execution insights to support alpha retention and execution optimization.

Key Responsibilities:

Conduct empirical research on trading performance and execution strategies to optimize the performance of various funds and mandates across Equities, Futures, and Options.
Enhance and support analytical databases and libraries for Transaction Cost Analysis (TCA). Perform deep-dive venue analysis to evaluate liquidity quality and routing logic.
Develop and maintain broker-side scorecards; design and execute A/B tests for new trading ideas and broker algorithms to drive continuous improvement.
Monitor global market structure developments and build tools to automate the production of market structure reports for Portfolio Managers and the trading desk.
Help build and maintain quantitative tools and libraries used for pre-trade estimation, post-trade evaluation, and market structure research.
Support and monitor trading done via the trading systems.

Desired Skills & Experience:

Advanced degree (Master's or PhD) in a quantitative field such as Mathematics, Physics, Computer Science, Financial Engineering, or Statistics.
3 to 10 years of experience in a quantitative research or trading role, preferably on the buy-side (Asset Management or Hedge Fund) or within a sell-side algorithmic execution team.
Excellent Python programming skills and strong understanding of software design and principles.
Experience with KDB+/Q or similar databases and tools for analyzing large data sets such as tick data.
Strong familiarity with advanced statistical modeling, machine learning, market dynamics modeling, and optimization techniques.
Familiarity with trading and market microstructure of Equities and at least one Futures or Options markets.
Good knowledge of various trade execution algorithms (e.g. VWAP/IS/Liquidity Seeking) and Transaction Cost Analysis (TCA).
Experience using generative AI and agentic AI tools to automate research workflows, code generation, and analytical tasks.
Strong communication skills, with the ability to translate complex quantitative findings into clear, actionable insights for various stakeholders, including Portfolio Managers.

Salary Range
The expected base salary for this New York, NY, United States-based position is $125000-$250000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

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.