About the Role
As Senior Manager, Measurement Analytics and Test Design, you will identify organizational learning goals, develop holistic omnichannel testing strategies, schedule organizational testing and communication plans and create and implement statistical testing procedures.
What You’ll Do
Lead the conversation on the scaling, persevering or shelving of marketing tactics
Design long-term testing strategies based on organizational learning initiatives
Manage the execution of tests and ensure the validity of results
Lead ad-hoc analysis for upcoming and in-flight campaigns and provide the approach for data modeling
Prepare aggregated testing results, generally tied to a learning initiative, for broad audiences
Drive organizational change through effective storytelling based on test results
Define the coding, model selection, visualization and analytical approach for research projects
Implement analytical processes and data models into production (e.g., Break Even modeling)
Lead the overall portfolio of process improvement opportunities and development of new capabilities
Own the measurement capability roadmap and align stakeholder needs with capabilities and processes
Design protocols and procedures for testing, including statistical models and execution standards
Facilitate improvement projects with internal teams and partners
Establish testing and analysis KPIs
Lead ad hoc modeling projects to develop machine learning solutions aimed at facilitating test design and informing target audiences for marketing tests
Lead the technical development of resources to meet measurement capabilities, including statistical analysis, coding (R, Python, SQL) and data visualization (Tableau, R)
Additional tasks may be assigned
What Skills You Have
Required
Master’s Degree in Data Science, Business, Statistics, Computer Science, Management Information Systems or similar
6+ years of experience
Advanced experience in SQL and knowledge of Excel functions
Deep understanding of statistical analysis, Data Mining and Machine Learning toolsets and methodologies
Extensive experience and knowledge of A/B test measurement and associated methodologies (incl. statistical tests, bias correction, propensity score modeling, et al.)
Experience with one or many object-oriented programming languages (R, Python, C++, Java, etc.) and the ability to write production-level programs
Background in utilizing data visualization tools (e.g., Tableau, PowerBI), and an advanced understanding of data visualization practices
Demonstrated project management skills
2+ years of experience in leading analytics or data science teams
Experience with designing testing programs
Preferred
Experience developing production-level Machine Learning/statistical algorithms