Job Reference #
Do you look at a scatterplot and see a story? Do you want to apply your expertise in coding to propel hypothesis-driven empirical research? Are you excited by the prospect of working in diverse teams with a broad range of skillsets?
We are looking for a Data Scientist to:
• build and maintain applications and tools that bring enterprise statistical computing to sell-side equity research
• help to ingrain replicable statistical computing workflows into the division's way of doing business
• collaborate with analyst teams to help them implement empirical research techniques to inform their investment thesis
• work with data and technology partners across the division
You’ll be working in the Empirical Scientific Approaches in Global Research team. We are bringing hypothesis-driven empirical methods and enterprise statistical computing practices to sell-side equity research. This is an opportunity to be part of a dynamic, creative, globally distributed team positioned at the center of one of the top equity research departments in the world.
As a candidate with the following attributes, you will have an excellent chance of success if you:
• Have significant experience or formal training in statistical computing (preferably Python)
• Have experience with key data manipulation and visualizations libraries in Python, such as numpy, pandas, and matplotlib
• Have experience in applying statistical techniques to extract information from data (for example, ordinary least squares regression, instrumental variables regression, logistic regression)
• Possess excellent interpersonal skills, are energetic and committed and have proven team working ability
• Are intellectually curious, creative, and an independent thinker with excellent verbal and written communication skills
• Pay close attention to detail
• Can work under pressure
• Have a demonstrated ability to work effectively under remote supervision
It would also be a major plus (but not required) if you:
• Have strong Microsoft Excel/office skills
• Have a baccalaureate degree in economics, quantitative sociology, demography, or related empirical social science field, with excellent results
• Are familiar with other techniques from machine learning and data science, including regression trees, random forests, gradient boosting machines, and neural nets
UBS is the world’s largest and only truly global wealth manager. We operate through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management and the Investment Bank. Our global reach and the breadth of our expertise set us apart from our competitors.
With more than 70,000 employees, we have a presence in all major financial centers in more than 50 countries. Do you want to be one of us?
At UBS, we embrace flexible ways of working when the role permits. We offer different working arrangements like part-time, job-sharing and hybrid (office and home) working. Our purpose-led culture and global infrastructure help us connect, collaborate, and work together in agile ways to meet all our business needs.
From gaining new experiences in different roles to acquiring fresh knowledge and skills, we know that great work is never done alone. We know that it's our people, with their unique backgrounds, skills, experience levels and interests, who drive our ongoing success. Together we’re more than ourselves. Ready to be part of #teamUBS and make an impact?
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.