Data Science (Generative AI) - Capital One Auto Finance

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. As a Data Scientist at Capital One's Auto Finance business, you’ll be part of a high performing modeling and analytics team that’s leading the next wave of disruption at a whole new scale. Our team has a relentless focus on the craft of modeling and innovation, 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. You’ll drive the heart of business by working on an array of impactful and exciting applications like customer lifetime valuation, product recommendation, fraud detection, and productivity improvement via Generative AI. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money. Leverage a broad stack of open source and cloud technologies to reveal the insights hidden within huge volumes of numeric and textual data. Drive the development of customer-facing Generative AI applications, including novel agentic AI solutions, by expertly finetuning Large Language Models and applying reinforcement learning. Build AI/ML solutions through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers. Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.
• Leverage a broad stack of open source and cloud technologies to reveal the insights hidden within huge volumes of numeric and textual data.
• Drive the development of customer-facing Generative AI applications, including novel agentic AI solutions, by expertly finetuning Large Language Models and applying reinforcement learning.
• Build AI/ML solutions through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

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 1 years of specialized experience in building GenAI applications with open source tools, beyond ChatGPT.
• At least 2 years of experience in NLP or Reinforcement Learning
• 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

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