Principal Associate, Data Scientist - AI Foundations

Capital One•McLean, VA

About The Position

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: In this role, you will: Partner with a cross-functional team of data scientists, software engineers, product managers, and designers to deliver AI powered products that customers love. Leverage a broad stack of technologies — PyTorch, Keras, TensorFlow, Scikit-learn, transformers, 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 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. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications in the area of deep learning, natural language processing and recommendation & personalization and seek 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. With an engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code to existing products. 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.

Requirements

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 5 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 3 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)

Nice To Haves

Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
Specialized experience in the fields of Information Retrieval, NLP, Data-centric AI, and Knowledge Graphs
At least 3 years’ experience in PyTorch/Tensorflow
At least 3 years’ experience with machine learning
At least 1 year of experience working with AWS

Responsibilities

Partner with a cross-functional team of data scientists, software engineers, product managers, and designers to deliver AI powered products that customers love.
Leverage a broad stack of technologies — PyTorch, Keras, TensorFlow, Scikit-learn, transformers, 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

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume