Global Banking & Markets Data Scientist Machine Learning Scientist, Marquee Sales Strats Associate

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.

OUR IMPACT

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 will 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

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

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 Marquees 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.

HOW YOU WILL FULFILL YOUR POTENTIAL

At Goldman Sachs our Engineers and Scientists dont 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 TensorFlow/PyTorch) Jupyter Trino SQL and gain exposure to graph database technologies.

RESPONSIBILITIES AND QUALIFICATIONS:

Responsibilities:

* Design build and maintain robust data pipelines for feature engineering and model training ensuring data quality scalability and explainability.
* Develop train and deploy state-of-the-art machine learning models with a strong focus on recommendation systems and signal generation to address complex problems in financial markets.
* Utilize and contribute to the development of graph databases and knowledge graphs to enrich data context uncover hidden relationships and make predictions.
* Conduct rigorous model evaluation A/B testing and monitoring to ensure optimal performance reliability and business impact of deployed models.
* Collaborate with product managers engineers and business stakeholders to translate complex analytical findings into clear actionable insights and integrate ML solutions into production systems.
* Stay abreast of the latest advancements in machine learning AI and data science and proactively identify opportunities to apply new techniques.
* Contribute to the teams overall technical growth and best practices.

Qualifications:

* Advanced degree (Masters or Ph.D.) in Computer Science Machine Learning Statistics Applied Mathematics or a related quantitative field.
* 2 years of proven expertise and hands-on experience in the full lifecycle of data science and machine learning projects from data ingestion and feature engineering to model deployment and monitoring in a production environment.
* Exceptional programming skills in Python with a command of data science libraries (e.g. Pandas NumPy Scikit-learn)
* Experience with big data technologies (e.g. Spark Trino Hadoop) and ideally cloud platforms (e.g. AWS GCP Azure) for scalable data processing storage and model deployment.

* Ideally having understanding and practical experience with graph databases (e.g. Neo4j Amazon Neptune ArangoDB) and knowledge graph construction querying (e.g. Cypher SPARQL) and utilization for feature enrichment.
* Strong understanding of statistical modeling experimental design and causal inference.
* Clear critical thinking concise writing skills and excellent communication skills with the ability to articulate complex technical concepts to diverse audiences.
* Self-starter with a creative hands-on approach to problem-solving and a passion for designing and implementing programmatic solutions to client needs.
* Able to thrive in a global fast-paced and collaborative team environment.