Data Scientist at Capital One leveraging technology to improve fraud prevention and customer safety. Collaborating with cross-functional teams to deliver industry-leading fraud defenses.
Responsibilities
Leverage a broad stack of technologies — Python, Conda, AWS, Spark, Gremlin, NeptuneDB, and more — to build knowledge graphs and graph algorithms that uncover hidden connections in structured and unstructured data
Pilot graph modeling algorithms through all phases of development, from design through training, evaluation, validation, and implementation
Connect your deep technical modeling expertise to the pressing business goals of our fraud prevention strategy partners to create exciting solutions to demanding challenges
Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading fraud defenses
Requirements
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 plus 3 years of experience performing data analytics
A PhD in a quantitative field
Master’s Degree in “STEM” field plus 3 years of experience in data analytics
At least 3 years’ experience with Knowledge Graphs or similar data
At least 1 year experience working with Graph database management (NeptuneDB, Neo4j, etc)
At least 1 year experience working with Graph query languages (Gremlin, Cypher, etc)
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 SQL
Benefits
Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits that support total well-being
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