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NEXTMOVEFDE careers · United States
Capital One (Plano campus)

Principal Associate, Data Scientist - Frontier AI in Customer Protection

AI summary of the role

This Principal Associate Data Scientist role on the Retail Bank Customer Protection team focuses on building knowledge graphs and graph algorithms to detect and prevent fraud and scams.

What you’ll do

  • Build knowledge graphs and graph algorithms using Python, Conda, AWS, Spark, Gremlin, NeptuneDB to 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 deep technical modeling expertise to pressing business goals of fraud prevention strategy partners
  • Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading fraud defenses

What you’ll bring

  • Bachelor's degree in a quantitative field plus 5 years data analytics experience, or Master's plus 3 years, or PhD
  • At least 3 years experience with Knowledge Graphs or similar data
  • At least 1 year experience with Graph database management (NeptuneDB, Neo4j, etc.)
  • At least 1 year experience with Graph query languages (Gremlin, Cypher, etc.)

Technologies

Python · Conda · AWS · Spark · Gremlin · NeptuneDB · SQL · Knowledge Graphs · Graph algorithms · Neo4j

Source and classification

Internal deployment & tooling · Evidence for this classification:

Data Science team has a relentless focus on innovation with a passion for improving customer experiences around fraud prevention. This team is focused on detecting and thwarting fraud and scams that target our customers and threaten their financial well-being and feelings of safety. Detecting and preventing fraud behaviors as early as possible helps keep customer funds secure and enables the Bank to grow with confidence. Our team is constantly investing to improve and complement existing model-based defenses with the latest and greatest techniques from industry and academia. We use data to proxy the real world signals that help us find fraud and engineer our way to using this in production with SQL and Python-centric methods. Role Description In this role, you will: Leverage a broad stack of technologies — Python, Conda, AWS, Spark, Gremlin, NeptuneDB, and more — to build knowledge
More from the job description

Principal Associate, Data Scientist - Frontier AI in Customer Protection 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 Retail Bank Customer Protection Data Science team has a relentless focus on innovation with a passion for improving customer experiences around fraud prevention. This team is focused on detecting and thwarting fraud and scams that target our customers and threaten their financial well-being and feelings of safety. Detecting and preventing fraud behaviors as early as possible helps keep customer funds secure and enables the Bank to grow with confidence. Our team is constantly investing to improve and complement existing model-ba [... source excerpt omitted ...] enses with the latest and greatest techniques from industry and academia. We use data to proxy the real world signals that help us find fraud and engineer our way to using this in production with SQL and Python-centric methods. Role Description In this role, you will: 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 [... source excerpt omitted ...] r with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading fraud defenses The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Technical. You’re comfortable with open-source languages and are passionate about developing further. Y

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