Principal Data Scientist

Principal Data Scientist

Data Scientist – Community Impact and Investment Team

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

The Community Impact and Investment team develops tools and insights to support our philanthropic investment  and product decisions with data-driven understanding of the communities we serve. In addition to internal decision-making, we conduct research on community impact topics that often lead to externally published articles. Our team is constantly exploring creative approaches using secondary data sources to generate meaningful insights on relevant community impact issues. 

In this role, you will:

• Partner with a cross-functional team of data scientists, software engineers, and business leaders to develop insights that drive community investments and financial well-being.

• Leverage a broad stack of technologies—Python, R, Conda, AWS, H2O, Spark, and more—to collect, clean, and analyze data from diverse sources.

• Develop and validate causal inference models to assess the social impact of internal community initiatives and relevant public programs.

• Solve data challenges creatively by sourcing and integrating alternative datasets, including government reports, survey data, and financial transaction data.

• Translate complex findings into clear, actionable recommendations for internal stakeholders and external partners.

The Ideal Candidate is:

• Mission-Driven. You’re passionate about leveraging data to make a positive social impact and believe in using insights to drive better decision-making.

• Innovative. You stay on top of the latest research in causal inference, machine learning, and data collection methodologies—and love applying them to real-world problems.

• Creative. You thrive in ambiguity, enjoy tackling undefined problems, and love finding novel data sources to enrich analysis.

• Statistically-Minded. You have experience with causal inference methods (RCTs, regression discontinuity, propensity score matching, difference-in-differences) and know how to interpret results from statistical models.

• Technical. You’re proficient in R and Python and comfortable working with large-scale datasets in cloud environments like AWS.

• A Data Guru. You know that great data science starts with understanding the data. You have experience retrieving, combining, and analyzing structured and unstructured data from various sources.

Basic Qualifications:

• Bachelor’s Degree plus 5 years of experience in data analytics, or Master’s Degree plus 3 years in data analytics, or PhD in a quantitative field

• At least 1 year of experience in open-source programming languages for large-scale data analysis

• At least 1 year of experience with machine learning

• At least 1 year of experience with research or data analysis

• At least 1 year of experience with relational databases

Preferred Qualifications:

• Master’s Degree in a STEM field (Science, Technology, Engineering, Mathematics) plus 3 years of experience in data analytics, or PhD in STEM

• At least 1 year of experience working with AWS

• At least 3 years of experience