Data Analyst

Key Responsibilities:

Tackle a set of analyses and documentation gaps to remediate varied risks on Commercial risk rating models across Commercial & Industrial and Commercial Real Estate models.
Produce well-organized and replicable code (Python or R) and other analysis artifacts that drive towards a clear analysis and support recommendations.
Summarize risk remediation in memoranda and make updates to the model whitepapers and to the model code prototypes.
Review analysis recommendations and conclusions in a timely manner with model team leadership and the Model Risk Office challengers and produce additional follow-Client as needed.

Key Requirements and Technology Experience:

Key Skills: Data Analysis, Python /R, SQL, Statistics/ Statistical Analysis.
Master’s Degree in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related discipline.
Alternatively, a bachelor's degree plus at least 5 years of experience in data analytics.
2+ years of experience with data analysis.
1+ years of experience with Python, R or other statistical analyst software.
Strong understanding of quantitative analysis methods in relation to financial institutions.
Ability to interact with challenge functions, with grounded analysis and clear assumptions and transparency of limitations.
Develop high quality and transparent model documentation.
Excellent coding skills in R and Python and drive to create efficient, accurate, and maintainable code with best practices.
Strong written and verbal communication skills.
Appreciation for processes, controls, and good governance.