Your role

Are you passionate about directly impacting the business by utilizing analytical and machine learning skills? Do you want to play a key role in mining large datasets, build advanced statistical models to generate meaningful and actionable insights, improve decision making, optimize the business process, and help address business problems?

We’re are looking for Data Scientist to:

• work with stakeholders to identify opportunities to leverage data to address business problems and drive business results
• mine and analyze data from various data sets to provide actionable insights
• build and deploy machine learning and statistical methods to optimize the business process and help with targeted marketing and sales efforts
• develop processes and tools to monitor and analyze model performance and data accuracy
• produce relevant documentation related to model performance, model review and model governance

Your Career Comeback

We are open to applications from career returners. Find out more about our program on ubs.com/careercomeback.

Your team

You will be part of the Data Science team in Smart Technologies and Advanced Analytics Team (STAAT), WMA in our New York City 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 global based in US, Poland, China, and Switzerland. We are open to Hybrid/remote work schedule. You’ll be able to witness day to day work of a data scientist, including data collection and curation, exploratory data analysis, model training and delivery. Depending on the project you’ll be involved in, you’ll be able to participate in different stages of model development and interacting with internal clients from different divisions.

Diversity helps us grow, together. That’s why we are committed to fostering and advancing diversity, equity, and inclusion. It strengthens our business and brings value to our clients.

Your expertise

• ideally a Master’s degree or PhD in Data Science, Machine Learning, Statistics, or related STEM fields
• ideally 5+ years of relevant or equivalent experience, experience in finance industry is a plus
• knowledge of a variety of machine learning techniques such as classification, clustering, optimization, Random Forest, PCA, XgBoost, natural language processing, deep neural network, etc
• good understanding of mathematical underpinning and their real-world advantages/drawbacks
• 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 Greenplum, DB2, Dataiku, Hadoop, etc
• hands-on experience deploying analytical models to solve business problems
• ability to develop experimental and analytical plans for data modeling processes and A/B testing
• experience with Tableau