Senior Manager, Data Scientist -Retail Bank Data Science Experimentation Lead
About The Position
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. The Retail Bank Data Science is establishing a centralized authority for experimental design to validate and prioritize competing hypotheses. As the DoE and Causal Inference Lead, you will act as a strategic force multiplier, ensuring that our product roadmap is validated through rigorous testing and providing a clear, defensible line of sight into the incremental value of our initiatives. You will lead the "Design of Experiments" center of excellence, bridging the gap between technical data science and business-line execution.
Requirements
- 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: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics
- A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics
- A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
- At least 2 years of experience leveraging open source programming languages for large scale data analysis
- At least 2 years of experience working with machine learning
- At least 2 years of experience utilizing relational databases
Nice To Haves
- PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
- At least 1 year of experience working with AWS
- At least 1 year of experience managing people
- At least 5 years’ experience in Python, Scala, or R for large scale data analysis
- At least 5 years’ experience with machine learning
Responsibilities
- Standardize how we measure incrementality across the organization to ensure metric improvements are tied to specific, isolated initiatives, reducing misattribution.
- Work with Product Managers and Business Analysts to design in-market tests early in the lifecycle, validating high-risk assumptions before full-scale development.
- Build the infrastructure for testing, including a centralized repository for hypotheses, known covariates, causal models, and results.
- Consult with Data Scientists and Analysts on advanced causal inference techniques for observational data where A/B testing isn't feasible.
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.
Benefits
- comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
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What This Job Offers
Job Type
Full-time
Career Level
Senior
