Capital One
Financial Services
PrincipalAssociate,DataScientist-USCardDFSAcquisitions
Neural analysis suggests this role is
optimal for Principal candidates.
“Principal Associate, Data Scientist - US Card DFS Acquisitions at Capital One. Skills: Machine learning models, Statistical modeling, Data analysis, Python, AWS. Build industry leading machine learning models to empower core underwriting decisions. Meet model risk standards”
What You'll Achieve.
Drive value; Deliver a product customers love
Industry & Context.
Creative problem solvers; Reveal the insights hidden within huge volumes of numeric and textual data; Understanding the data is often the key to great data science
What They're Looking For.
Must Have
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, 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, PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)
Nice to Have
Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, 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
What You'll Do.
Build industry leading machine learning models to empower core underwriting decisions
Meet model risk standards
Enable COF model use in acquisition area integration
Support increased scaling volume
Bring key DFS insights (data
or models) into the COF building
Refit key models combining COF and Discover populations
Own the full life cycle of our models - development
and ongoing usage expansion and releases
Deliver a product customers love
Leverage a broad stack of technologies 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
Translate the complexity of your work into tangible business goals
How You'll Work.
Team & Collaboration
Partner with a cross-functional team of data scientists, software engineers, and product managers; Collaborate closely with a wide range of cross functional partner teams - data engineers, platforms engineers, product managers, credit and business analysts; Work with stakeholders to identify and improve the status quo
Communication Scope
Translate the complexity of your work into tangible business goals
Full 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 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. ****Role Desc
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