Join Capital One as a Manager, Data Scientist - Card Risk

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

About Us

Data is at the center of everything we do at Capital One. From our humble beginnings as a startup that disrupted the credit card industry in 1988 to our current status as a Fortune 200 company, our passion for data has led us to become leaders in data-driven decision-making. We have continuously evolved, now utilizing the latest computing and machine learning technologies to manage billions of customer records and create personalized financial solutions.

Team Description

As part of the Card Risk Data team, you will collaborate with the Card Risk organization to develop machine learning solutions. You'll uncover actionable insights from large sets of unstructured data and work with various teams across the enterprise to ensure our company remains well-managed and profitable.

Role Description

In this role, you will:

• Develop end-to-end innovative data science solutions to solve business challenges and accelerate stakeholder adoption.
• Collaborate with data analysts, risk professionals, software engineers, and product managers to manage risks and make informed decisions.
• Utilize a broad stack of technologies, including Python, Conda, Flask, Dash, Hugging Face, LangChain, AWS, H2O, and Spark, to extract insights from vast quantities of numeric and textual data.
• Build machine learning and NLP models, from design to implementation, ensuring scalability and high performance.
• Create and manage data pipelines and validate frameworks and quality tests.
• Explore new technologies to enhance data management, model development, and enterprise ML products.
• Effectively translate complex data science work into tangible business goals.

Ideal Candidate

The ideal candidate is:

• Innovative: Continuously researches and evaluates emerging technologies and seeks opportunities to apply them.
• Creative: Excels at defining and solving big, undefined problems and is comfortable sharing new ideas.
• Technical: Proficient with open-source languages and passionate about developing further, with hands-on experience in developing data science solutions.
• Collaborative and Communicative: Capable of articulating data insights and strategies to a diverse audience.
• Statistically-minded: Experienced in building, validating, and back testing models, with knowledge of clustering, classification, sentiment analysis, time series, and deep learning.
• Data Guru: Skilled at retrieving, combining, and analyzing data from various sources and structures.

Basic Qualifications

Currently has, or is in the process of obtaining:

• Bachelor’s Degree with 6 years of experience in data analytics, or
• Master’s Degree with 4 years of experience in data analytics, or
• PhD with 1 year of experience in data analytics, with an expectation that the degree will be obtained on or before the scheduled start date

Additionally:

• At least 2 years’ experience in open source programming languages for large-scale data analysis
• At least 2 years’ experience with machine learning
• At least 2 years’ experience with relational databases

Preferred Qualifications

• PhD in a STEM field (Science, Technology, Engineering, or Mathematics) with 3 years of experience in data analytics
• At least 1 year of experience working with AWS
• At least 4 years’ experience in Python, Scala, or R for large-scale data analysis
• At least 4 years’ experience with machine learning
• At least 4 years’ experience with SQL

Additional Information

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being. Visit the to learn more. Eligibility varies based on full or part-time status, exempt or