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. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and relational databases, cutting-edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time, and agony in their financial lives. The US Card Management Data Science team builds industry-leading machine learning models to empower core underwriting decisions in the management of an existing credit card customer, such as credit limit increases. We collaborate closely with a wide range of cross-functional partner teams - data engineers, platforms engineers, product managers, credit and business analysts, to deliver the solutions from ideation to implementation. We are a team of model developers, who own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases. We are also a team of creative problem solvers, who challenge the status quo on a continuous basis and are devoted to innovation to keep making our models more dynamic, adaptive, robust, and ultimately, smarter. In this role, you will partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love. You will leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data. You will build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation. You will flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Responsibilities

  • Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.
  • Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal insights hidden within huge volumes of numeric and textual data.
  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
  • Translate the complexity of your work into tangible business goals.

Requirements

  • Currently has, or is in the process of obtaining a Bachelor's Degree plus 2 years of experience in data analytics, or currently has, or is in the process of obtaining Master's Degree, 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 a STEM field (Science, Technology, Engineering, or Mathematics), or PhD in a STEM field.
  • Experience working with AWS.
  • At least 2 years' experience in Python, Scala, or R.
  • At least 2 years' experience with machine learning.
  • At least 2 years' experience with SQL.

Benefits

  • Comprehensive health benefits
  • Financial benefits including performance-based incentives
  • Inclusive set of benefits supporting total well-being
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