Quantitative Research Analyst – Equity Valuation Model

Job Description

HOLT Model Development Analyst | UBS

The Tone:
This is a full-time role at UBS, located in Chicago, IL. UBS is a leading and truly global wealth manager, the leading universal bank in Switzerland, and provides diversified asset management solutions and focused investment banking capabilities across more than 50 markets. This role is critical to the HOLT Model team within Equity Research, which is recognized as an industry leader for understanding corporate performance and equity valuation. The analyst will play a key part in enhancing a systematic equity valuation model that serves a strong client franchise of major institutional investors, hedge funds, and wealth managers.

The TL;DR
• Role: Early Career
• Type: Full Time
• Location: In-person, Chicago, IL
• Pay: $145000–$172500 yearly
• Team: HOLT Model team within Equity Research
• Mission: To advance the HOLT systematic equity valuation model and its analytical capabilities for clients.
• Tech Stack: R, SQL, Python

What You’ll Actually Do
• Research Development: Conduct empirical and academic style research to further develop the HOLT systematic equity valuation model and its downstream analytics.
• Performance Analysis: Analyze company life cycle dynamics, encompassing growth, profitability, and competitive landscapes.
• Tool Creation: Develop new quantitative scorecards, frameworks, and datasets specifically for client use.
• Methodology Enhancement: Research and enhance valuation methodologies, including cash flow forecasting, alternative scenarios, and the interaction between company fundamentals, valuation, and market environments.
• Framework Validation: Assist in designing, testing, and validating enhancements to the HOLT framework using its extensive financial dataset dating back to the 1950s.

The Must-Haves
• Background: Hold a BS or MS in Accounting, Finance, Economics, Engineering, Mathematics, or another quantitative field, coupled with an understanding of financial statements, company valuation, and equity markets.
• Experience: Ideally possess 1-5 years of relevant experience, with practical experience using R, SQL, or Python for data analysis.
• Skills: Demonstrate strong quantitative and analytical abilities, expertise in analyzing large datasets, and excellent written and verbal communication skills for publishing long-form research.
• Bonus: Familiarity with Databricks and Spark is advantageous, along with experience in statistical analysis, forecasting techniques, or financial data modeling. Curiosity to explore how AI can improve workflows, validating outputs and aligning with policies, risk standards, and ethical use, is also a plus.