Capital One
Financial Services
PrincipalAssociate,DataScientistUSCardDFSAcquisitions
“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
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