Senior Associate, Data Scientist - People Strategy & Analytics

Capital One•McLean, VA

1d•Onsite

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 People Strategy & Analytics brings data, analytics, and insights to shape critical talent decisions and strategy at Capital One. We work closely with HR partners and senior executives in shaping talent policy, automating real-time data, and improving talent decision-making. The team is comprised of people with diverse skills and backgrounds including: data analysts, data scientists, business analysts, HR specialists, project managers, and industrial/organizational psychologists. As a Data Scientist on Capital One’s People Strategy & Analytics team, you’ll be on the leading edge of applying analytics to talent, combining artificial intelligence, machine learning, and social science to build models that seek to understand associate behavior, improve HR efficiency and tools, and inform strategies aimed at expanding Capital One’s talent advantage.

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 2 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

Nice To Haves

Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
Experience working with AWS
At least 2 years’ experience in Python
At least 2 years’ experience with machine learning
At least 2 years’ experience with SQL
At least 1 year experience with relational databases such as Snowflake
At least 1 year experience with AI/ML tools and ecosystems such as Hugging Face, VectorDBs or Pytorch/TensorFlow

Responsibilities

Support development of natural language processing and machine learning models through all phases, from design through training, evaluation, validation, and implementation
Apply expertise in using open source large language models (LLMs) through prompt engineering, retrieval-augmented generation (RAG) and evaluation metric frameworks for business specific applications
Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading HR tools and AI-powered products
Leverage a broad stack of technologies — Python, SQL, AWS, LangChain, Hugging Face Transformers, VectorDBs, Pytorch/TensorFlow, and more — to reveal the insights hidden within large volumes of numeric and textual data
Flex your interpersonal skills to collaborate with internal stakeholders, translating complex data science work into tangible, aligned business outcomes.