Principal Data Scientist - The Capital One Lab

Center 1 (19052), United States of America, McLean, Virginia

Principal Data Scientist - The Capital One Lab

Principal Data Scientist - The Capital One Lab

At Capital One, we think big and do big things. We are a Top-10 bank by deposits—a high-tech company, scientific laboratory, and a nationally recognized brand. Our products reach tens of millions of consumers and have been recognized by numerous prestigious awards for their customer-friendliness. Capital One was the first major bank to move to cloud computing and to publish APIs for the Open Banking future. AI is transforming every industry, at Capital One you will help shape how it transforms financial services.

Team Description

The Capital One Lab is a passionate and entrepreneurial team embracing bold ideas, fostering collaboration, and delivering great experiences for our customers. The Lab is tasked with building next-generation products and services for Capital One and transforming how we get work done at the company. The Lab was the first place in the company to use cloud services, data science, hackathons, and design thinking – all practices that define work at the company today. This work is core to Capital One’s mission, changing banking for good! 

As a Principal Data Scientist in the Lab you’ll be tasked with exploring new business opportunities with data and ML. The ideal candidate for this role is passionate about technology and deeply empathizes with internal and external customer needs. They are comfortable in conversation with product and engineering teams. They work well with UX researchers on early explorations, designers on concrete user journeys and flows, as well as stakeholders from different lines of business, Legal, Cyber, Enterprise Supplier Management (ESM), and others.

Role 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 — Python, PyTorch, AWS, HuggingFace, VectorDBs, and more — to reveal the insights hidden within huge volumes of structured and unstructured 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:

• A data guru. “Big data” doesn’t faze you. You have the skills to research, 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.

• 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.

• 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.

• 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 are highly collaborative and have the ability to influence and lead.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date

• At least 1 year of experience in exploring internal and external datasets, formulating hypotheses, executing a plan with open source programming languages, visualizing and communicating results.

• At least 1 year of experience building machine learning models through all phases of development, from design through training, evaluation, validation, implementation, and monitoring.

Preferred Qualifications:

• 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)

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