Senior Manager, Data Analysis

Capital One Capital One · Banking · Richmond, VA +1

Senior Manager, Data Analysis role at Capital One, focusing on validating enterprise-wide analytical tools, assessing their quality and risk, and prototyping industry best practices. Requires experience in data analytics, leading open-source data technologies, and people management. The role is within the financial services industry and involves working with data-driven decision-making processes.

What you'd actually do

  1. Refining a new Enterprise-wide analytical tools validation framework
  2. Planning and executing validation projects
  3. Assessing the quality and risk of analytical tool methodologies across Capital One, and the nature of tools usage within those processes
  4. Understanding technical issues in analytical tools and assessing tools risks and opportunities
  5. Independently researching, identifying, and prototyping industry best practices for emerging analytical tools

Skills

Required

  • Bachelor’s Degree in quantitative field plus at least 7 years of experience performing data analytics, or Master’s Degree plus at least 5 years of experience performing data analytics
  • At least 5 years of experience performing professional data analysis work
  • At least 5 years of experience leading and developing with open source data technologies
  • At least 2 years of experience managing people

Nice to have

  • Master’s Degree or PhD in a Finance, Economics, Statistics, Mathematics, Industrial Engineering, Operations Research, or a related field
  • At least 7 years of experience in statistical or econometrics hands-on work
  • At least 5 years of experience manipulating and performing analysis with large data sets
  • At least 5 years of experience in financial services industry
  • At least 5 years of experience in developing statistical or econometric models
  • At least 5 years of experience in validating statistical or econometric models
  • At least 2 years of experience with data governance
  • At least 2 years of experience with predictive analytics

What the JD emphasized

  • analytical tools validation framework
  • assessing the quality and risk of analytical tool methodologies
  • prototyping industry best practices for emerging analytical tools