Director, Data Scientist - Generative AI 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 The Generative AI Systems (Genesis) team within Card Data Science builds state-of-art, generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing as well as time-series sequencing modeling. We partner with product, tech and design teams to deliver internal applications based on these solutions that drive efficiency in our business and data analytics teams, as well as customer-facing applications that enhance the customer experience. You will lead a seasoned group of natural language processing (NLP), speech, and computer vision specialists, experimenting with emerging technologies in generative AI, delivering software implementing these technologies, and contributing research to major NLP and AI/ML conferences. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money. Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features. Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate is: 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. 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. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond. 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. 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 9 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 7 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 4 years of experience performing data analytics At least 4 years of experience leveraging open source programming languages for large scale data analysis At least 4 years of experience working with machine learning At least 4 years of experience utilizing relational databases Preferred Qualifications PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics At least 1 year of experience working with AWS At least 3 years of experience managing people At least 5 years of experience in Python, Scala, or R for large scale data analysis At least 5 years of experience with machine learning 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: $269,100 – $307,200 for Dir, Data Science New York, NY: $293,600 – $335,100 for Dir, 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 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. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. 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. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at View phone number on click.appcast.io or via email at View email address on click.appcast.io. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One’s recruiting process, please send an email to View email address on click.appcast.io Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). #J-18808-Ljbffr