Manager, Data Scientist, Travel Intelligence, Flights

Capital OneMcLean, VA
$197,300 - $245,600

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 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. Team Description You will be a member of the Travel Intelligence team, a high-impact group dedicated to building the "intelligent core" of Capital One Travel. Our mission is to transform vast amounts of travel data into intelligent, personalized, and seamless experiences for our customers. Specifically, this role focuses on the Flights domain, where you will own end-to-end technical strategy to build robust, in-house machine learning. From creating new fintech products, to optimizing fare pricing and flight sorting, this team directly impacts the customer experience and the business's bottom line. Our goal is to leverage our massive amounts of historic and live-updating flight data to create innovative fintech solutions in the travel space. Role Description 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 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

Requirements

  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 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 4 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) plus 1 year of experience performing data analytics
  • At least 1 year of experience leveraging open source programming languages for large scale data analysis
  • At least 1 year of experience working with machine learning
  • At least 1 year of experience utilizing relational databases

Nice To Haves

  • PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
  • At least 1 year of experience working with AWS
  • At least 5 years’ experience in Python, Scala, or R for large scale data analysis
  • At least 5 years’ experience with machine learning

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 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

Benefits

  • 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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