I wrote efficient SQL queries to contribute tidy tables to the data warehouse and to support experiments and visualizations.I designed, monitored, and analyzed experiments which improved conversion, app engagement, and retention via relevant messaging.I shared analytic insights to audiences of diverse seniority and technical aptitude.I collaborated with data engineering to ingest raw marketing data which we used to mature our attribution tables.I was the SME for our org’s Looker instance; developed year-ago analysis capabilities.

I contributed to and cleaned data warehouse tables using dbt.I developed a customer grain multi-touch attribution model and Looker dashboard which is used daily to drive tactical ad spend decisions and backward-looking insights.I developed an LTV/CAC dashboard which was powered by a user-level multitouch attribution model; this was used to empower senior leadership to better understand and act upon long-term value of marketingI served on the Diversity, Equity, and Inclusion council

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)

I designed and continually maintained an Excel spreadsheet with the purpose of monitoring the performance of clients’ portfolios; the spreadsheet received positive feedback and is still in use. I also prepared monthly and quarterly reports for high net-worth clients’ portfolios which were presented to both the clients and the firm’s partners. I researched equities and annuities via Morningstar Advisor to give input for investment options—which positively affected clients’ returns.I was frequently assigned the above projects concurrently and completed them in a timely manner.