About The Position

Principal Associate, Data Scientist - Specialist Models 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 AI 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 Specialist Models team builds AI and machine learning models that help our customers and lines of businesses get timely & accurate recommendations, reduce friction and prevent fraud . We build Recommendation systems, AI Search Systems, Summarization tools, RAG based systems, and Agentic AI systems, using LangChain, LangGraph, PyTorch on AWS environment. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver products customers love Leverage a broad stack of technologies — Python, Conda, AWS, frontier Foundation Models, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data Build AI and machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals 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. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. 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.

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 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

Responsibilities

  • Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver products customers love
  • Leverage a broad stack of technologies — Python, Conda, AWS, frontier Foundation Models, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
  • Build AI and machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals
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