Manager, Data Scientist - Business Cards & Payments
About The Position
Capital One’s Business Card & Payments Data Science team develops machine learning models for credit underwriting decisions. The models support emerging business card product strategies and form part of the company’s credit infrastructure. The team builds modeling solutions across customer life cycles and collaborates with business stakeholders, product teams, and software and machine learning engineering teams to address problems and develop long-term modeling strategies. In this role, you will partner with data scientists, software engineers, and product managers to deliver customer-focused products. You will use technologies such as Python, Conda, AWS, H2O, and Spark to uncover insights in large volumes of numeric and textual data. You will build machine learning models throughout their development lifecycle, including design, training, evaluation, validation, and implementation, and communicate how your work supports business goals. The ideal candidate is customer-focused, technically capable with open-source tools and cloud computing platforms, creative in addressing ambiguous problems, and statistically minded. Relevant modeling experience includes validation and backtesting, interpreting confusion matrices and ROC curves, and applying clustering, classification, sentiment analysis, time-series methods, and deep learning.
Requirements
- Currently hold, or be in the process of obtaining by the scheduled start date, a bachelor's degree in a quantitative field plus 6 years of data analytics experience; or a master's degree in a quantitative field, or an MBA with a quantitative concentration, plus 4 years of data analytics experience; or a PhD in a quantitative field plus 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.
Nice To Haves
- PhD in a STEM field plus 3 years of data analytics experience.
- At least 1 year of experience working with AWS.
- At least 4 years of experience using 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.
- Experience developing and validating models, backtesting, interpreting confusion matrices or ROC curves, and using clustering, classification, sentiment analysis, time series, or deep learning.
Responsibilities
- Partner with data scientists, software engineers, and product managers to deliver products customers love.
- Use technologies such as Python, Conda, AWS, H2O, and Spark to find insights in large volumes of numeric and textual data.
- 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.
- Collaborate with business stakeholders, product teams, and software and machine learning engineering teams to develop modeling solutions and long-term modeling strategy.
Benefits
- Comprehensive health, financial, and other benefits supporting total well-being; eligibility varies by employment status and management level.
- Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
