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UBS
New York, New York, United States
(on-site)
Job Type
Full-Time
Data Scientist
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Data Scientist
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Description
Job Reference #338676BR
Business Divisions
Global Wealth Management
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
Title
Data Scientist
City
New York
Job Type
Full Time
Country / State
United States - New York
Function Category
Digital, Product Management and Development
Join us
At UBS, we know that it's our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We're dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That's why collaboration is at the heart of everything we do. Because together, we're more than ourselves.
We're committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.
Disclaimer / Policy statements
UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.
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
About us
UBS is a leading and truly global wealth manager and the leading universal bank in Switzerland. We also provide diversified asset management solutions and focused investment banking capabilities. Headquartered in Zurich, Switzerland, UBS is present in more than 50 markets around the globe.
We know that great work is never done alone. That's why we place collaboration at the heart of everything we do. Because together, we're more than ourselves. Want to find out more? Visit ubs.com/careers.
How we hire
We may request you to complete one or more assessments during the application process. Learn more
Salary information
The indicative gross base salary range as a full-time equivalent role:
• United States - New York - New York min USD 72500 - max USD 93000 /annum
The expected salary for this role will be determined by relevant factors which may include but are not limited to, role-required experience, qualifications, education, location and skill level. UBS offers a range of competitive benefits and for further information, please visit ubs.com/employee-benefits. We may, at our sole discretion, provide additional variable compensation or awards.
Requisition #: 338676BR
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Job ID: 84573097

UBS
United States
UBS draws on its 150-year heritage to serve private, institutional and corporate clients worldwide, as well as retail clients in Switzerland. We combine our wealth management, investment banking and asset management businesses with our Swiss operations to deliver superior financial solutions.
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Median Salary
Net Salary per month
$5,203
Cost of Living Index
100/100
100
Median Apartment Rent in City Center
(1-3 Bedroom)
$4,299
-
$9,615
$6,957
Safety Index
49/100
49
Utilities
Basic
(Electricity, heating, cooling, water, garbage for 915 sq ft apartment)
$120
-
$472
$244
High-Speed Internet
$50
-
$100
$73
Transportation
Gasoline
(1 gallon)
$3.63
Taxi Ride
(1 mile)
$3.49
Data is collected and updated regularly using reputable sources, including corporate websites and governmental reporting institutions.
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