Manager, Data Science - US Card Customer Management

About the role

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 join a team that’s leading the next wave of disruption at massive scale, using the latest computing and machine‑learning technologies across billions of customer records to unlock opportunities that help everyday people save money, time, and frustration in their financial lives.

Team description

Part of the US Card data science organization, this team focuses on the customer‑management business and builds top‑tier machine‑learning solutions for real‑time customer behavioral prediction and valuation forecasts. We work collaboratively with cross‑functional partners including business stakeholders, engineers, analysts, data‑science/quants, and product managers.

Responsibilities

• Partner with a cross‑functional team of data scientists, software engineers, and product managers to deliver products customers love.
• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to uncover insights hidden within massive numeric and textual datasets.
• Build machine‑learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Translate complex technical work into tangible business goals using strong interpersonal skills.

Ideal candidate

• Customer first: Passionate about analyzing and creating solutions that benefit customers.
• Innovative: Continuously research emerging technologies and apply state‑of‑the‑art methods.
• Creative: Thrive on defining and solving large, ambiguous problems; eager to share new ideas.
• Leader: Challenge conventional thinking, collaborate with stakeholders, and develop talent.
• Technical: Proficient with open‑source languages and cloud platforms; hands‑on experience delivering data‑science solutions.
• Statistically‑minded: Experience building, validating, and back‑testing models; comfortable interpreting confusion matrices, ROC curves, clustering, classification, sentiment analysis, time series, and deep learning.
• Data guru: Skilled at retrieving, combining, and analyzing data from diverse sources and structures.

Basic qualifications

• Either:
  • Bachelor’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) + 6 years of data‑analytics experience, or
  • Master’s degree in a quantitative field (or MBA with quantitative concentration) + 4 years of data‑analytics experience, or
  • PhD in a quantitative field + 1 year of data‑analytics experience.
• 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) + 3 years of data‑analytics experience.
• At least 1 year of experience working with AWS.
• At least 4 years of experience in Python, Scala, or R for large‑scale data analysis.
• At least 4 years of experience with machine learning.
• At least 4 years of experience with SQL.

Pay

Cambridge, MA: $197,300 – $225,100 for Manager, Data Science
McLean, VA: $197,300 – $225,100 for Manager, Data Science
New York, NY: $215,200 – $245,600 for Manager, Data Science
Richmond, VA: $179,400 – $204,700 for Manager, Data Science

Candidates hired in other locations will receive the pay range associated with that location. The role is also eligible for performance‑based incentive compensation, which may include cash bonuses and/or long‑term incentives.

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being. Eligibility varies based on full‑ or part‑time status, exempt or non‑exempt status, and management level.