
location_onNYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
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 relational databases in 1988. Fast-forward a few years, and this innovation and our passion for data have 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 will be part of a team leading the next wave of disruption at a whole new scale. We use the latest computing and machine learning technologies to operate across billions of customer records, unlocking opportunities that help everyday people save money, time, and stress in their financial lives.
The Generative AI Systems (Genesis) team within Card Data Science builds state-of-the-art, generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series sequencing modeling. We partner with product, tech, and design teams to deliver internal applications that drive efficiency in our business and data analytics teams, as well as customer-facing applications that enhance the customer experience. You will work with 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.
In this role, you will partner with a cross-functional team to deliver products customers love. You will leverage a broad stack of technologies to reveal insights hidden within huge volumes of numeric and textual data, building machine learning models through all phases of development from design through implementation. A key part of your success will be flexing your interpersonal skills to translate the complexity of your work into tangible business goals.
The ideal candidate is customer-first, passionate about doing the right thing for our customers. You are creative, thriving on bringing definition to big, undefined problems and pushing hard to find answers. As a leader, you challenge conventional thinking, work with stakeholders to improve the status quo, and are passionate about talent development for your own team and beyond. You are technically comfortable with open-source languages and cloud computing platforms, with a passion for developing further.
This role is expected to accept applications for a minimum of 5 business days. No agencies please. If you require an accommodation to apply, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to the extent required to provide needed reasonable accommodations.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. We promote a drug-free workplace and will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws. Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being.
Skills: Generative Ai, Statistical Modeling, Relational Database, Machine Learning, Natural Language Processing, Speech Recognition, Computer Vision, Time-Series Sequencing Modeling, Python, Kubernetes.
Education: Bachelor's Degree in a quantitative field required with 7 years experience; Master's Degree in a quantitative field or MBA with quantitative concentration required with 5 years experience; PhD in a quantitative field required with 2 years experience.
Work model: On-site
NYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
New York, New York
PhD in a STEM field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics. At least 1 year of experience working with AWS. At least 1 year of experience managing people. At least 5 years' experience in Python, Scala, or R for large scale data analysis. At least 5 years' experience with machine learning.
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