Quantitative Model Development Analyst

UBS; Chicago (IL); On-site; USD 145,000 - 172,500; Full time

Job summary

UBS in Chicago, IL, is seeking a research-focused professional to advance the HOLT systematic equity valuation model and downstream analytics. You will develop new quantitative scorecards, analyze life cycle dynamics, and enhance methodologies for forecasting and valuation, using large datasets.

Ideal candidates have 1–5 years of experience, strong quantitative skills, and proficiency in R/SQL/Python. Excellent communication skills and ability to publish long-form research are valued.

Qualifications

• Curious to explore how AI can improve workflow build, delivery, and optimization.
• BS or MS in accounting, finance, economics, engineering, mathematics, or another quantitative field.
• Ideally 1–5 years of relevant experience.
• Strong quantitative and analytical skills with experience analyzing large datasets.
• Understanding of financial statements, company valuation and equity markets.
• Experience with R, SQL, or Python.

Responsibilities

• Conduct empirical and academic style research to further develop valuation models and analytics.
• Analyze company life cycle dynamics, including growth, profitability and competitive dynamics.
• Develop new quantitative scorecards, frameworks and datasets for client use.
• Research and enhance methodologies including cash flow forecasting and macro interactions.
• Assist in designing, testing and validating enhancements to the framework using UBS data.
• Contribute to published research and internal documentation communicating findings.

Skills

Quantitative analysis

Data analysis

Communication skills

Self-motivated

Team-oriented

Financial statements understanding

Education

BS/MS in quantitative field

Tools

R

SQL

Python

Databricks

Spark

Job description

UBS in Chicago, IL, is seeking a research-focused professional to advance the HOLT systematic equity valuation model and downstream analytics. You will develop new quantitative scorecards, analyze life cycle dynamics, and enhance methodologies for forecasting and valuation, using large datasets.

Ideal candidates have 1–5 years of experience, strong quantitative skills, and proficiency in R/SQL/Python. Excellent communication skills and ability to publish long-form research are valued.