Principal Associate, Data Scientist - People Strategy & AnalyticsData 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 DescriptionPeople 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.Role DescriptionIn this role, you will:Build natural language processing and machine learning models through all phases of development, from design through training, evaluation, validation, and implementationApply expertise in using open source large language models (LLMs) through prompt engineering, retrieval-augmented generation (RAG) and evaluation metric frameworks for business specific applicationsPartner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading HR tools and AI-powered productsLeverage 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 dataFlex your interpersonal skills to collaborate with internal stakeholders, translating complex data science work into tangible, aligned business outcomes.The Ideal Candidate is:Passionate about human capital: You are excited by the value we can add to our company and our associates, and are inspired to help make a large positive impact.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.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.Statistically-minded.
You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.Basic Qualifications: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 analyticsA Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 3 years of experience performing data analyticsA PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)Preferred Qualifications: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 AWSAt least 3 years' experience in PythonAt least 3 years' experience with machine learningAt least 3 years' experience with SQLAt least 2 years' experience with relational databases such as SnowflakeAt least 2 years' experience with AI/ML tools and ecosystems such as Hugging Face, VectorDBs or Pytorch/TensorFlow