Skip to content
NEXTMOVEFDE careers · United States
Capital One (Plano campus)

Principal Associate, Data Scientist - US Card DFS Acquisitions

AI summary of the role

This Principal Associate Data Scientist role on the US Card DFS Acquisitions Integration team builds machine learning models for credit card underwriting decisions, combining Capital One and Discover populations.

What you’ll do

  • Partner with cross-functional teams (data scientists, software engineers, product managers) to deliver customer-facing products
  • Leverage Python, Conda, AWS, H2O, Spark to extract insights from large numeric and textual datasets
  • Build machine learning models through all phases: design, training, evaluation, validation, and implementation
  • Translate complex technical work into tangible business goals for stakeholders

What you’ll bring

  • Bachelor's degree in quantitative field plus 5 years data analytics experience, or Master's plus 3 years, or PhD
  • 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

Technologies

Python · Conda · AWS · H2O · Spark · SQL · Scala · R · machine learning · deep learning

Source and classification

Internal deployment & tooling · Evidence for this classification:

Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions of a new credit card customer. The team is responsible for meeting model risk standards and enabling COF model use in acquisition area integration policies; supporting increased scaling volume by bringing key DFS insights (data, features, or models) into the COF ecosystem; building or refitting key models combining COF and Discover populations to drive value. 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
More from the job description

Principal Associate, Data Scientist - US Card DFS Acquisitions 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 The US Card DFS Acquisitions Integration Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions of a new credit card customer. The team is responsible for meeting model risk standards and enabling COF model use in acquisition area integration policies; supporting increased scaling volume by bringing key DFS insights (data, features, or models) into the COF ecosystem; building or refitting key models combining COF and Discover populations to drive value. We collaborate clos [... source excerpt omitted ...] status quo on a continuous basis and are devoted to innovation to keep making our models more dynamic, adaptive, robust, and ultimately, smarter. 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 o [... source excerpt omitted ...] You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. Basic Qualifications: 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 5 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathemati

How jobs are selected

Employer postings · Data from · Sources