Quantitative Analytics Associate - Controllership

KeyBankBrooklyn, OH
1d$68,000 - $103,000

About The Position

As part of the Risk Modeling Enablement team within Finance, responsibilities for this position include, but are not limited to: Supporting the implementation, testing, documentation, and on-going validation of credit loss forecasting models for use in CECL Allowance and Capital Stress Testing Coordinating with Lines of Business, Data Owners, Risk Management, and Key Technology, Operations, and Services (KTOS) to ensure alignment with all activities impacting credit loss models Creating and/or maintaining production environments for ongoing credit loss forecasting, including creation of process controls Working both independently and as part of cross-functional teams to perform business, data, and application analysis to implement business requirements on a variety of reporting needs and strategic project initiatives This role requires developing close relationships with the model development and reporting groups and understanding the impact of changing portfolio characteristics as well as economic and financial environments on model results. The position will require the ability to understand various statistical methodologies used to forecast credit losses, to complete analysis supporting critical business processes, and to understand and access various data sources, analytical platforms, and reporting platforms, including the use of cloud interfaces for programming and engineering.

Requirements

  • Bachelor’s Degree (Math, Statistics, Data Analytics, Computer Science, Finance, Accounting or related degree preferred)
  • Two years of relevant accounting, finance, analytics, or modeling experience, or a graduate degree in a related field
  • Proficiency in Python (e.g., NumPy, Pandas) or other Object-Oriented Programming language
  • Database querying and data transformation experience (e.g., Excel, BigQuery, DB2)
  • Familiarity with building reporting dashboards, including through the use of Tableau, Google Looker Studio, or other similar tools
  • Experience dealing with complex and large data sets from multiple sources to support analytical processes
  • Excellent communication skills
  • Quantitative, analytical, problem solving, and decision-making skills
  • Detail-focused organizational skills required to coordinate and manage multiple tasks simultaneously to meet strict deadlines

Nice To Haves

  • Experience with Git, and demonstrable coding best-practices
  • Familiarity with Cloud Analytics (e.g., Google Cloud Platform, Azure, AWS)
  • Experience with quantitative modeling or forecasting
  • Familiarity with Current Expected Credit Loss financial accounting standards
  • Experience with bank stress testing (e.g., CCAR, DFAST)
  • Familiarity with ReactJS

Responsibilities

  • In working with other teams within Finance, support orderly maintenance and development of a Google Cloud Platform (GCP) environment for model development and deployment
  • Assist with design of and implementation of production applications for credit loss modeling
  • Gather client requirements and translate to technical specifications; working closely with Risk Management Information Reporting (RMIR) and KTOS teams on changes to the production CECL environment, system conversions, quarterly change cycles, technical error resolution, production support, and other enhancements
  • Critical participation in annual Capital Plan Stress Tests, working closely with groups across the organization to produce and vet Credit Loss and Allowance forecasts
  • Perform data and process validation during development, testing, and production phases of various projects, including maintaining detailed records of development process
  • Communicate key points to respective stakeholders, with the appropriate level of detail for the relevant partners
  • Continue to evolve processes and use of technology with a focus on continuous improvement, leveraging new technologies, and identifying and implementing efficiencies; working with teammates and partners to document and ensure use of best coding practices
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