Capital One - McLean, VA

posted 5 months ago

Full-time - Mid Level
McLean, VA
101-250 employees
Credit Intermediation and Related Activities

About the position

Data is at the center of everything we do at Capital One. As a Principal Associate, Data Scientist in the Model Risk Office, you will play a crucial role in defending the company against model failures and enhancing decision-making processes through advanced statistical modeling and data analysis. This position is not just about crunching numbers; it’s about leveraging data to drive strategic decisions that impact millions of customers. You will collaborate with a diverse team of data scientists, software engineers, and product managers to identify and quantify risks associated with various models, ensuring that our methodologies are robust and reliable. In this role, you will utilize a wide array of technologies, including Python, AWS, and Spark, to extract insights from large datasets. Your responsibilities will include building and validating statistical and machine learning models that challenge existing champion models currently in production. You will also contribute to the governance of next-generation machine learning models, ensuring they meet the highest standards of accuracy and reliability. Your ability to communicate complex model risks to executives will be essential, as you will need to present findings in a clear and impactful manner. The ideal candidate for this position is someone who is innovative and continuously seeks to learn about emerging technologies and methodologies. You should be comfortable with open-source programming languages and have a strong foundation in statistical analysis. Your experience should include building and validating models, as well as a deep understanding of data retrieval and analysis from various sources. This role is perfect for someone who thrives in a fast-paced environment and is passionate about using data to solve real-world problems.

Responsibilities

  • Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models.
  • Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal insights hidden within data.
  • Build statistical/machine learning models to challenge 'champion models' that are deployed in production today.
  • Contribute to the model governance of the next generation of machine learning models.
  • Present how model risks could impact the business to executives.

Requirements

  • Currently has, or is in the process of obtaining a Bachelor's Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master's Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date.
  • At least 1 year of experience in open source programming languages for large scale data analysis.
  • At least 1 year of experience with machine learning.
  • At least 1 year of experience with relational databases.

Nice-to-haves

  • Master's Degree in 'STEM' field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in 'STEM' field (Science, Technology, Engineering, or Mathematics).
  • At least 1 year of experience working with AWS.
  • At least 3 years' experience in Python, Scala, or R.
  • At least 3 years' experience with machine learning.
  • At least 3 years' experience with SQL.
  • At least 1 year of experience building or validating models to detect financial crimes (Fraud Detection, Anti-Money Laundering).

Benefits

  • Comprehensive health insurance coverage
  • Financial benefits including 401k and profit sharing
  • Paid time off and holidays
  • Professional development opportunities
  • Diversity and inclusion programs
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