Company: WeAreTechWomen
Location: London
Posted: March 19th, 2026
As a Data Scientist/Machine Learning Scientist in the Global Markets Division, you will be at the forefront of innovation on the trading floor. You will design and implement advanced machine learning models, including predictive AI, to uncover complex market trends and generate actionable insights. Leveraging cutting‑edge techniques, you will develop sophisticated analytical tools that, at scale, connect clients to the signals, tools and expertise to better analyze their portfolios and manage risk. Your expertise will drive data‑driven product development and business strategy through advanced analytics, predictive modelling, and the application of recommendation systems. Our data scientists and machine learning engineers are applying advanced quantitative and AI/ML techniques to solve the most complex business challenges in a dynamic, entrepreneurial team with a passion for the markets.
Marquee is Goldman Sachs’ premier digital platform for Global Banking & Markets, serving our Institutional and Corporate clients with the latest insights and analytics from the division. A recognized market leader, Marquee has garnered 5 awards over the past 3 years for its innovative solutions.
The Marquee Sales Strats team is a hub for advanced data science and machine learning, focusing on developing and deploying predictive AI, recommendation systems, and sophisticated analytical models. We leverage extensive datasets, including those structured in graph databases and knowledge graphs, to generate deep insights into financial markets and enhance Marquee’s platform engagement. We collaborate closely with Sales, Trading, Engineering, Product, Design, and other areas of the Global Markets Division, and directly with clients. Our global team comprises experts in financial markets, product structuring, cutting‑edge technology, and advanced data science/machine learning, including specialists in graph theory and knowledge representation.
As a Marquee Sales Data Scientist/Machine Learning Scientist, you will be instrumental in designing, developing, and deploying advanced machine learning models, including predictive AI and recommendation systems, to deliver unparalleled analytics and insights for the Goldman Sachs Franchise. Your work will directly enhance the client experience and drive strategic decision‑making. You will collaborate closely with Traders, Salespeople, and Strats across all asset classes, leveraging your expertise to build robust data pipelines, engineer impactful features, and train sophisticated models. Your contributions will be critical in developing personalized recommendation engines and predictive analytics that drive Marquee platform adoption and ensure clients receive the most relevant, timely, and actionable content. You will utilize technologies including Python (Pandas, Polars, Scikit‑learn, TensorFlow/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies.
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Qualifications:
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.
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: Disabled Candidate Statement.
© The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.
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