Job Description

Manager, Data Scientist - Recommendation & Personalization Systems 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 Join an elite Applied AI team within AI Foundations, operating at the intersection of deep research and massive real‑world impact. We are pioneering the next generation of personalized customer experiences across Capital One’s web and mobile applications, leveraging our high‑scale ML models. Our core mission involves architecting and deploying cutting‑edge personalized recommendation engines. This is powered by original research into homegrown Foundation Models, advanced Reinforcement Learning techniques, and a state‑of‑the‑art scalable architecture built for billions of interactions. Our research agenda is at the forefront of the field, actively focusing on areas such as Causal Inference, Transformer‑based architectures, and sophisticated Recommender Systems. Responsibilities Partner with a cross‑functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. 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. 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. A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. 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 6 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 4 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) plus 1 year of experience performing data analytics At least 1 year of experience leveraging open‑source programming languages for large‑scale data analysis At least 1 year of experience working with machine learning At least 1 year of experience utilizing relational databases Preferred Qualifications PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics At least 3 years of hands‑on experience building, deploying, and maintaining high‑scale, production‑grade ML systems using MLOps practices, including AWS, Kubeflow, and CI/CD pipelines At least 4 years of experience in developing and optimizing state‑of‑the‑art Deep Learning models, specifically Transformer‑based architectures, using PyTorch and distributed training with multi‑GPU optimization At least 4 years of experience with high‑performance, distributed data processing for petabyte‑scale feature engineering using frameworks like DASK and PySpark Salary and Benefits McLean, VA: $197,300 – $225,100; New York, NY: $215,200 – $245,600; San Jose, CA: $215,200 – $245,600. 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 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. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. Equal Employment Opportunity Statement Capital One is an equal‑opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. #J-18808-Ljbffr

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