Manager, Data Scientist - Credit Review

About

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 relational databases, cutting‑edge technology in 1988. Fast‑forward a few years, and this innovation and our passion for data have propelled us to a Fortune 200 company and a leader in 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 computing and machine learning technologies across billions of customer records to unlock big opportunities that help everyday people save money, time, and agony in their financial lives.

Team Description

In Capital One’s Credit Review Models, Data and Innovative Solutions team, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We invest in the future by building better tools, developing new skills, and maintaining a network of trusted partners. We partner with best‑in‑class data scientists, analysts, credit risk management experts, and engineers to innovate solutions that directly impact the company’s bottom line in a meaningful way. Our collaborative environment values individual insight, encourages each associate to take on new responsibilities, promotes continuous learning, and rewards innovation.

Role Description

In this role, you will:

• Leverage a broad stack of technologies (e.g., Python, Conda, AWS, H2O, Spark) to reveal insights hidden within huge volumes of numeric and textual data.
• Build statistical and machine learning models to challenge the models in production.
• Translate the complexity of your work into tangible business goals using strong interpersonal skills.
• Partner with a cross‑functional team of data scientists, credit risk experts, and product managers to deliver a product customers love.

Ideal Candidate

• Technical: Comfortable with open‑source languages and passionate about development; hands‑on experience building data science solutions using open‑source tools and cloud platforms.
• Statistically‑minded: Built, validated, and back‑tested models; able to interpret confusion matrices and ROC curves; experienced with clustering, classification, sentiment analysis, time series, and deep learning.
• Innovative: Continuously research and evaluate emerging technologies; stay current on state‑of‑the‑art methods and seek opportunities to apply them.
• Creative: Thrive on defining big, undefined problems; ask questions, push hard for answers, and share new ideas.

Basic Qualifications

• 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:
  • Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 6 years of experience performing data analytics.
  • Master’s Degree in a quantitative field (or an MBA with a quantitative concentration) plus 4 years of experience performing data analytics.
  • PhD in a 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.

Preferred Qualifications

• PhD in a STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics.
• 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 predictive modeling.