Goldman Sachs
Website:
goldmansachs.com
Company:
https://www.linkedin.com/company/goldman-sachs
Seniority: Associate
Industries: Financial Services
Job details:
Job Description
WHO WE ARE
The Goldman Sachs Group, Inc. is a leading global financial services firm providing investment banking, securities and investment management services to a substantial and diversified client base that includes corporations, financial institutions, governments and high-net-worth individuals. The firm is headquartered in New York and maintains offices in London, Frankfurt, Tokyo, Hong Kong and other major financial centers around the world.
YOUR IMPACT
As a Strat within the Global Banking & Markets Division, you will be the primary architect of the data ecosystem that powers the Credit Systematic Market Making (SMM) desk. This role is a unique blend of quantitative analysis, systems engineering, and emerging technology applied to algorithmic trading in Credit products.
You will be responsible for the end-to-end lifecycle of the desk's data—from sourcing and outlier detection to long-term curation—while combining your programming, mathematical, and market expertise to help generate systematic trading strategies. This position is designed for a high-performing individual who wishes to master the foundations of systematic trading, with a clear trajectory toward quantitative research and AI-driven strategy development.
GLOBAL BANKING & MARKETS DIVISION
Our core value is building strong relationships with our institutional clients, which include corporations, financial service providers, and fund managers. We help them buy and sell financial products on exchanges around the world, raise funding, and manage risk. This is a dynamic, entrepreneurial team with a passion for the markets, with individuals who thrive in fast-paced and changing environments.
Job Summary
Candidates joining the Credit Systematic Market Making (SMM) team will focus on the quantitative data foundation that drives our electronic market making in Credit products. The desk offers liquidity primarily in a principal capacity and trades with clients via vendor.
We are looking for "Data Strats" who understand that high-quality research starts with high-quality data. You will be responsible for sourcing diverse financial datasets and implementing rigorous cleaning and normalization protocols, while also contributing to the quantitative improvement of trading strategies and market microstructure analysis.
While your initial focus will be on data, this role offers a structured path to research. As you demonstrate mastery of the desk's data and pricing logic, you will have the opportunity to participate in research projects, eventually transitioning into a research-oriented role where you will leverage advanced AI tooling to develop systematic trading strategies.
Responsibilities
- Lead the sourcing and ingestion of internal and external datasets. Explore and deploy AI-driven tools to automate the identification of outliers and maintain "research-ready" datasets.
- Automate common desk workflows and streamline the trading process to improve efficiency and scalability.
- Understand and analyze market microstructure, incorporating findings into data pipelines and trading strategies.
- Collaborate with the broader research team to leverage your "Golden Source" datasets for backtesting. Over time, take ownership of specific research workstreams and contribute quantitative improvements to existing trading models.
- Actively research and trial new AI technologies to improve data integrity and generate alpha, keeping the desk at the forefront of technological innovation.
Basic Qualifications
- Strong programming proficiency in Python (required) and C++ or Java
- Bachelors or Masters in a STEM area (Computer Science, Mathematics, Physics, or Engineering)
- Experience in quantitative data cleaning, ETL processes, and managing large-scale time-series datasets.
- Experience building large software systems and working with large data sets.
- A strong interest in algorithmic trading and in applying AI/ML techniques to financial data and market mechanics.
Preferred Qualifications
- Experience with KDB+/Q or other high-performance time-series databases.
- Familiarity with fixed income pricing models and market microstructure.
- Past experience developing large, scalable systems.
- Demonstrated interest in transitioning into quantitative research through personal projects or prior experience.
GOLDMAN SACHS ENGINEERING CULTURE
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers .
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html©
The Goldman Sachs Group, Inc., 2026. All rights reserved.
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity
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