Senior Associate, Data Scientist - People Strategy & Analytics

Senior 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. 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. In this role, you will: 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 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, staying current on published state‑of‑the‑art methods, technologies, and applications, and seeking 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 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 Preferred Qualifications: Master’s Degree in a STEM field (Science, Technology, Engineering, or Mathematics), or PhD in a STEM field 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 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. Salaries for part‑time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $135,600 – $154,800 for Sr Assoc, Data Science This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI). Incentives could be discretionary or non‑discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23‑A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901‑4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. #J-18808-Ljbffr Information Technology Senior Management Forum