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Lead Quantitative Analytics Associate - Model Monitoring in Cleveland, OH at KeyBank

Date Posted: 11/20/2020

Job Snapshot

Job Description

For its quantitative modeling and analytics group within the Finance organization, KeyCorp is looking for a Lead Quantitative Associate to develop model performance monitoring and testing frameworks for predictive models. This individual independently builds and performs qualitative and quantitative assessments of all aspects of the models including theoretical aspects, model design and model performance as well as data quality and integrity.

This individual will assist with model monitoring projects, including but not limited to developing performance metrics for econometric, credit risk, and other types of statistical models. This individual will use quantitative tools and techniques to measure and analyze model risks, and establish conclusions on strengths and limitations of the model.

Under some supervision, the Lead Quantitative Analytics Associate is primarily responsible for using statistics, advanced mathematical techniques, and/or computer science to develop and validate predictive and machine-learning models for specific business needs. The Lead Quantitative Analytics Associate leverages advanced mathematical knowledge and analysis to provide solutions to predictive and prescriptive questions such as “What will happen next?” and “What will we do?”. Often large in scope, projects undertaken by the Lead Quantitative Analytics Associate involve self-directed data analysis and model building in response to a problem statement proposed by a business partner. Success factors include: timely and effective completion of tasks assigned by manager with manager and/or peer guidance; exercising functional knowledge in analytical programming languages, data literacy, and model development; effective communication of insights and data to peers; and developing work autonomy and problem-solving.
  • Conduct quantitative analysis including hypothesis testing and root-cause analysis on large data sets with more autonomy
  • Support the working group by identifying types of information needed for analysis or to inform business questions create data structures/transformations to be leveraged by groups for analysis
  • Use statistical analysis and machine learning to develop, maintain, and anticipate considerations in implementation of models that address the right business need
  • Use critical thinking to use the right approach for each problem statement
  • Anticipate business need and make continuous improvements to models and processes
  • Bachelor’s degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 2 years of relevant experience; 1+ years’ experience with Master’s or PhD
  • DATA LITERACY - Understanding of and ability to:
    • Create data structures / transformations
    • Identify and capture different types of information for business needs or necessary for analysis
    • Data controls
    • Hypothesis testing / root-cause analysis
    • Leverage and anticipate considerations in implementation
    • Advanced Microsoft Office Suite
    • SQL/NoSQL
      • Relationship data structure
      • Selecting and retrieving data including unstructured data retrieval, archival, and ETL
      • Databases
    • Advanced Python/R/SAS:
      • Databases
      • Efficient coding
      • Can build strong code controls and translate code into high-level commentary
    • Understanding of and ability to leverage:
      • Cloud-based computing
    • Distributed computing
    • Understanding of:
      • Model use, requirements, and implementation needs
      • Model Risk Management process and foundations
      • Testing for deterioration and model health
      • Scale and fundamental concepts of Machine Learning
      • How statistical measurements are used
      • Advanced data techniques for modeling frameworks
    • Ability to:
      • Produce and identify information through statistical analysis
      • Effectively explain model insights to peers and analytics community
    • Identify preferred approach given the problem statement
  • Relational databases and SQL programming
  • Working knowledge of statistical/econometric analysis software such as R, Python, or SAS
  • Financial modeling in mathematical/symbolic terms
  • Experience creating Tableau dashboards
  • Ability to analyze complex financial instruments, create spreadsheets and write code to facilitate the analysis
  • Strong organization skills are required to perform multiple tasks simultaneously to meet strict deadlines
  • Proficiency in the use of Microsoft Office with advanced experience in Excel
  • The ability to understand generally accepted accounting principles


KeyCorp is an Equal Opportunity and Affirmative Action Employer committed to engaging a diverse workforce and sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.


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