Credit Model Development Quantitative Expert
$123,600–$206,000 year
On-siteBuffalo, New York, United States
Job Summary
Develop and validate complex econometric, statistical, and machine learning models for classification, clustering, and pattern analysis. Mentor less experienced data scientists on best practices for data sourcing, cleaning, and preventing data drift. Lead code reviews to ensure efficiency and adherence to industry standards while committing code to shared repositories. Own relationships with data clients to define research questions and adapt techniques based on specific needs. Implement internal controls and self-healing frameworks to mitigate risk in alignment with regulatory standards. Communicate actionable insights and model outcomes to cross-functional groups to influence business direction.
Required Qualifications
- Bachelor's degree
- Minimum of 6 years' proven quantitative behavioral modeling experience
- Minimum of 6 years' on-the-job experience with pertinent statistical software packages (SAS, Python, Stata, R)
- Minimum of 6 years' on-the-job experience with data management environment, such as SQL Server Management Studio
- Minimum of 6 years' on-the-job experience analyzing large data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs
- Experience with various hybrid databases both on premise and in the cloud
- Experience analyzing and explaining results of large data sets analyses
Desired Qualifications
- Masters' of Science or Doctorate degree in statistics, economics, finance or related field in the quantitative social, physical or engineering sciences, with proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management
- Minimum of 8 years' statistical analysis programming experience
- Financial Risk Manager (FRM) or Chartered Financial Analyst (CFA) designation
- Fluency and high proficiency in econometric/statistical techniques, especially time-series analysis, panel data methods and logistic regression
- Experience in balance sheet management and mathematical modeling of financial instruments offered by banks
- Knowledge and familiarity with key aspects of model risk management and model validation, including SR-11-7 guidance on model risk management
- Proven track record for being able to work autonomously and within a team environment
- Proven leadership skills
- Strong desire to learn and contribute to a group
- Previous experience leading and directing the work of less experienced personnel
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