Principal Statistician
San Francisco, California, Us
I led a small, cohesive teams in creating actionable statistical insights for key stakeholders to inform strategic marketing budgetary decisions. This entails using Hierarchical Bayesian modeling to build and maintain systems of panel data regressions (Marketing Mix Models). My clients averaged over 28 billion in revenue in 2018 and saw an average revenue growth of 8% since 2017.I accomplish this by:• Communicating cross-functionally to determine clients’ needs and scope out the project and delivery plan• Writing Python scripts to perform tasks such as data manipulation, EDA, and dimensionality reduction, leading to a standardized report causing efficiency gains and consistent decision-making• Building Hierarchical Bayesian Panel Data Regressions and leverage models to drive insights and recommendations by identifying underperforming and underspent media channels• Acting as subject matter expert to communicate findings to internal and external audiences of varying sizes and technical capabilitiesI have experience building these marketing solutions in a number of industries, including Automotive, e-Commerce, Financial Services, Home Improvement, Omni-Channel Retail, QSR, and TransportationIn addition to the above, I:• Developed training materials for a cross-functional quarterly training initiative, supporting the org’s first standardized onboarding curriculum• Manage a team of two’s career trajectory and day-to-day tasks• Was promoted from Associate Statistician to Statistician (Jan 2016) to Senior Statistician (June 2017) to Principal Statistician (Sep 2018)