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About the Role
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 Tech is a close-knit team of 480+ dedicated, talented and diverse individuals focused on delivering exceptional experiences and tech innovations for Capital One's associates and business partners.
Responsibilities
- 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, 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.
- Translate the complexity of your work into tangible business goals.
Requirements
- Experienced in taking models into production through the model risk compliance process
- Customer first mindset, focused on making the right decision for customers.
- Continually research and evaluate emerging technologies, staying current on published state-of-the-art methods.
- Thrive on bringing definition to big, undefined problems and asking questions to find answers.
- Challenge conventional thinking and work with stakeholders to identify and improve the status quo.
- Comfortable with advanced ML and DL technologies including language models, with hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.
- Passionate about AI/ML and able to bring along a cross functional team in breakthrough innovations.
- Communicate clearly and effectively to share findings with non-technical audiences.
- Experienced in training language models or large computer vision models.
- Expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF.
- Engineering mindset with a track record of delivering models at scale both in training data and inference volumes.
- Experience in delivering libraries, platforms, or solution level code to existing products.
- Currently have, or be in the process of obtaining 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.
- Currently have, or be in the process of obtaining 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.
- Currently have, or be in the process of obtaining 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.
Skills
- Natural Language Processing (NLP)
- Large Language Models (LLMs)
- Pytorch
- AWS Ultraclusters
- Hugging Face
- LangChain
- VectorDBs
- Machine Learning
- Deep Learning
- Open source programming languages
- Relational databases
- Python
- Scala
- R
- SQL
- AWS
Location
- McLean, VA
- New York, NY
- Plano, TX
Work Type
- Full-time
Experience Level
- 6 years of experience performing data analytics (with Bachelor's)
- 4 years of experience performing data analytics (with Master's/MBA)
- 1 year of experience performing data analytics (with PhD)
- 1 year of experience leveraging open source programming languages for large scale data analysis
- 1 year of experience working with machine learning
- 1 year of experience utilizing relational databases
- 4 years of machine learning experience
- 4 years of AI modeling experience
- 4 years of experience in Python, Scala, or R
- 4 years of experience with SQL
Education Level
- Bachelor's Degree in a quantitative field
- Master's Degree in a quantitative field or an MBA with a quantitative concentration
- PhD in a quantitative field
- PhD in STEM field
Salary/Compensations
- McLean, VA: $197,300 - $225,100
- New York, NY: $215,200 - $245,600
- Plano, TX: $179,400 - $204,700
Benefits
- Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
About the Company
- 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.
Equal Opportunity
- 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.