Principal Associate, Data Scientist - People Strategy & Analytics

Principal Associate, Data Scientist - People Strategy & Analytics 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. Role Description In this role, you will: • Build natural language processing and machine learning models through all phases of development, 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. 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 analytics • A 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 analytics • A 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 AWS • At least 3 years’ experience in Python • At least 3 years’ experience with machine learning • At least 3 years’ experience with SQL • At least 2 years’ experience with relational databases such as Snowflake • At least 2 years’ experience with AI/ML tools and ecosystems such as Hugging Face, VectorDBs or Pytorch/TensorFlow Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligi