Global Banking & Markets - Data Scientist​/Machine Learning Scientist, Marquee Sales Strats

Are you a visionary Data Scientist or Machine Learning Scientist passionate about leveraging cutting-edge AI to transform financial markets? Do you thrive on building end-to-end solutions, from robust data pipelines and sophisticated feature engineering to deploying advanced predictive models and personalized recommendation systems? If you have hands‑on experience, and a desire to make a significant impact in a dynamic, fast‑paced environment, we want to hear from you.

The Global Markets Division

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 Clients (Hedge Funds, Asset Managers, Insurers) 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, 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.

At Goldman Sachs, our Engineers and Scientists don’t just make things – we make things possible. Change the world by connecting people and capital with ideas and technology. Combine advanced engineering and deep market knowledge to solve the most pressing problems for our clients. We look for creative collaborators who evolve, adapt to change, and thrive in a fast‑paced global environment.

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, Tensor Flow/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies.

• Design, build, and maintain robust data pipelines for feature engineering and model training, ensuring data quality, scalability, and explainability.
• Develo…