Capital One-posted 3 months ago
$158,600 - $181,000/Yr
Full-time • Mid Level
McLean, VA
Credit Intermediation and Related Activities

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 the relational database, 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 Acquisitions Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions of a new credit card customer. 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.

  • 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 the 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.
  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals.
  • Currently has, or is in the process of obtaining a Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics.
  • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics.
  • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).
  • 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.
  • Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
  • Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
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