Your role
Your role Are you passionate about directly impacting the largest wealth management business in the world by utilizing AI? Do you want to play a key role in build AI and machine learning models to generate meaningful and actionable insights, improve decision making, optimize the business process, and help address business problems? Are you excited about opportunities Generative AI can bring for Wealth Management?
We are looking for a Data Scientist to:
• work with stakeholders to identify opportunities to leverage AI and machine learning to support Wealth Management business
• use Generative AI and agentic systems to improve business outcomes
• analyze and explain financial data from various sources to provide actionable insights for Financial Advisors and their Clients
• build and deploy machine learning and statistical methods to optimize the business process and help with targeted marketing and sales efforts for financial products
• using machine learning and generative AI to understand, explain and guide client investment decisions
• produce relevant documentation related to model performance, model review and model governance
• independently manage projects
Your team
UBS has been named Best Wealth Management Firm for Use of AI in the US at the Financial Times' PWM Wealth Tech Awards in 2026 for our work in STAAT.
You will be part of the Data Science team in Smart Technologies and Advanced Analytics Team (STAAT), WMA in our New York location. Our Data Science team is at the heart of STAAT's function to manage and support data science efforts across different business areas. Our team is globally based in US, Poland and India. At the heart of this project is the ability to systematically analyze and build AI and machine learning models with a goal for the Wealth Management business to make optimal decisions.
Your expertise
• master's degree or PhD in Computer Science, Data Science, Statistics, or related STEM fields
• 3+ years of relevant or equivalent experience, experience in finance industry is a plus
• knowledge of natural language processing, deep neural network, Generative AI and agentic systems
• knowledge of a variety of machine learning techniques such as classification, clustering, optimization
• hands on experience of using programming languages (Python, R, SQL, etc.) to manipulate data, develop models and derive insights
• hands on experience of database and analytical technologies in the industry, such as Postgres, Greenplum, Hadoop, etc.
• experience with Tableau/Power BI will be an asset
