Capital One
Retail Bank
SeniorManager,DataScientistRetailBankDataScienceExperimentationLead
“Senior Manager, Data Scientist -Retail Bank Data Science Experimentation Lead at Capital One. Skills: Design of Experiments, Causal Inference, Data Science Experimentation, Machine Learning, Statistical Modeling. Standardize how we measure incrementality across the organization. Design in-market tests early in the lifecycle to validate high-risk assumptions”
What You'll Achieve.
Ensure metric improvements are tied to specific, isolated initiatives; Validate and prioritize competing hypotheses; Provide a clear, defensible line of sight into the incremental value of our initiatives; Deliver a product customers love
Industry & Context.
Making the right decision for our customers; Reducing misattribution; Validating high-risk assumptions
What They're Looking For.
Must Have
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, 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, 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 Have
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
What You'll Do.
Standardize how we measure incrementality across the organization
Design in-market tests early in the lifecycle to validate high-risk assumptions
Build the infrastructure for testing
including a centralized repository for hypotheses
Consult with Data Scientists and Analysts on advanced causal inference techniques for observational data where A/B testing isn't feasible
How You'll Work.
Team & Collaboration
Partner with a cross-functional team of data scientists, software engineers, and product managers; Work with Product Managers and Business Analysts; Consult with Data Scientists and Analysts
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