Principal Associate, Data Science
About The Position
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-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 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 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. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. A data guru. “Big data” doesn’t faze you. 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.
Requirements
- 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, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)
Nice To Haves
- Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
- 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
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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
