Developed an Amazon Advertising and Seller Partner API driven Python-based pipeline to deliver accurate and reliable data that powers client-facing campaign and product reports

Created a prototype of Predictive Impact Capability for Design Engineering, utilizing various statistical analysis and modeling techniques to connect engineering choices and process steps to assembly and certification issues downstream

Co-founder and CDO responsible for everything to do with data, including sourcing, ingestion, storage, statistical analysis and modeling, and working with platform engineers to productize the results. Also responsible for compliance with GDPR.

Built the first iteration of statistical models that fit a person's behavioral profile based on a psychometric assessment to a particular job role. Worked closely with the engineering team to deploy the functionality in the production client-facing UI.

Worked on building out POSSIBLE's eCommerce Analytics practice. Created automated reporting flows that utilized product data from Amazon.com as well as a number of third party providers to provide clients with visibility and deeper insight into both organic and sponsored search rankings for their products. Also developed sophisticated methodology for determining which types of keywords included in product titles and descriptions on Amazon carry the most weight in terms of revenue.

Managed all things Data, while providing technical domain expertise, particularly in Analytics and Data Mining. Technical product management, planning and strategy, partner management.

Led the Engineering team and developed and managed the data ingestion and processing pipeline as well as internal and external-facing analytics.

Designed and managed both our internal and client-facing analytics. Collaborated with various internal and external teams to develop an in-depth understanding of the business needs that can be addressed with data, turning this into product design, and working with engineering to make it happen. Provided ongoing custom data analysis support to address questions not covered by existing features, and incorporate the learnings into future product strategy.

Analyzed huge datasets collected from hundreds of millions of users playing Zynga games all over the world. Wrote complex SQL queries to extract the data stored in a Vertica data warehouse and squeezed meaning out of it using R and Tableau, applying advanced analysis techniques, including Machine Learning algorithms. Member of the CityVille launch team.

Was responsible for various reporting and data analysis tasks revolving around user experience using eBay search. Wrote complex SQL queries that directly accessed the Teradata-based Data Warehouse and analyzed results in Excel and (mostly) R. Created email reports on eBay visitors, heat maps of the search results page usage, and performed ad hoc deep dives. Introduced the Site Analytics group to R and conducted several training sessions.

Data mining using SQL database queries, R for data visualization and analysis, and Python and UNIX shell scripting for task automation. Studied short and long-term visitor behavior patterns that directly affected business decisions. Worked with every team in the company, providing custom reports and ad hoc analyses.