Capital One - Cambridge, MA

posted 4 months ago

Full-time - Senior
Cambridge, MA
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 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. Consumer Identity ML is the data science and machine learning team inside Capital One's AI foundation organization. We deliver real-time, personalized, intelligent customer experiences in Capital One's suite of award-winning digital products, including our website, mobile app, emails, chatbot, and beyond. We partner closely with our product and engineering teams to build the data and modeling platforms crucial to the deep understanding of customers that enables our applications to delight them by adapting to their needs. As part of Consumer ML, you will explore billions of clickstream events to discover the patterns in customer behavior, and use those patterns to model key customer outcomes. You will develop the real-time models that use vast amounts of customer data to anticipate customers' needs and deliver the right options at the right time. Additionally, you will develop the models that ensure our most important customer data is accurate, fighting fraud and other bad behavior, while enabling seamless digital experiences across all our products. In Consumer Identity ML, you will work at all phases of the data science life cycle, including building machine learning models through all phases of development, from design through training, evaluation and validation, and partnering with engineering teams to improve operationalization in scalable and resilient production systems that serve 50+ million customers. You will partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention. You will also write software (Python, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark.

Responsibilities

  • Explore billions of clickstream events to discover patterns in customer behavior and model key customer outcomes.
  • Develop real-time models that use vast amounts of customer data to anticipate customer needs and deliver the right options at the right time.
  • Ensure the accuracy of important customer data to fight fraud and enable seamless digital experiences across all products.
  • Build machine learning models through all phases of development, from design through training, evaluation, and validation.
  • Partner with engineering teams to improve operationalization in scalable and resilient production systems serving 50+ million customers.
  • Conduct experiments with various business and product teams to guide improvements to customer experiences and business outcomes.
  • Write software in Python to collect, explore, visualize, and analyze numerical and textual data using tools like Spark.

Requirements

  • Currently has, or is in the process of obtaining a Bachelor's Degree plus 7 years of experience in data analytics, or currently has, or is in the process of obtaining a Master's Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 2 years of experience in data analytics.
  • At least 3 years' experience in open source programming languages for large scale data analysis.
  • At least 3 years' experience with machine learning.
  • At least 3 years' experience with relational databases.

Nice-to-haves

  • PhD in a 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 1 year of experience managing people.
  • At least 5 years' experience in Python, Scala, or R for large scale data analysis.
  • At least 5 years' experience with machine learning.

Benefits

  • Comprehensive health benefits
  • Financial benefits including performance-based incentives
  • Inclusive workplace policies
  • Support for total well-being
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