Lead marketing and product analytics team at this consumer-finance firm; responsible for building in-house multi-touch attribution (MTA) model, developing analytics road map & deploying site analytics solution - Performed customer journey analysis of 20+ million individual visitors to develop insights into behavior across web properties and over multiple digital touches; identified paths with 2X – 3X higher yield - Coded automation scripts (Python) for reporting & data processing tasks, reducing delivery time by 90%+ - Designed and developing statistical attribution models to report lift and optimize TV spend across channels - Provided recommendation and planned deployment of new site tagging and tracking tool across all sites - Led selection process for Identity-Resolution vendor including PoC; performed log-file analysis of CRM, site visits and phone calls to determine strength of person/device identity graph for use in MTA modeling - Designed cross-functional quarterly planning process for Analytics, coordinating across Marketing, Data Engineering & Product to publish first roadmap; significantly improved delivery to 98% of commitment

My team includes data scientists, data analysts and business analysts focused on building predictive models to drive customer experiences (personalization, targeting and value-optimization), customer/marketing analytics (marketing mix, multi-touch attribution), contact management (life-cycle and trigger-based) and a newly-formed test-and-learn center of excellence. - Directed contact management team in core dataset redesign and streamlining standard reporting using an agile development process, improving on-time delivery and reducing report development time by 80%+ - Led successful development and launch of a Test-and-Learn Center-of-Excellence (CoE), deploying a new digital testing process and tool across four retail brands; focused on driving both velocity & impact- Designed multivariate tool to calculate the impact of $100M TV spend on website organic & SEM traffic- Prototyped tool in R/Shiny to assess impact of opening/closing stores to both online and retail store sales

Performance reporting, payment volume forecasting and variance analysis for US Product group- Conceptualized, designed and led cross-functional technical team to build Hadoop data mart using Agile development; delivered project on-time and under-budget, reducing data processing time by 95%+- Led annual planning process for new product initiatives, coordinating across multiple groups and stakeholders to develop metrics-based forecasts of payment volumes and revenues- Built forecasting model to predict payment volumes for launch of $90B+ cobrand credit card; accurately anticipated key unknown metrics using combination of public and proprietary data sources- Analyzed impact of severe weather on consumer behavior using geographic analysis; identified $800M payment volume loss from single storm and established framework for future weather impact analyses- Developed forecast model for product penetration of consumer debit, mobile wallet POS and API-based payment enablement for global ecommerce payment platform

Marketing analytics, predictive modeling, business forecasting and performance reporting- Managed development of marketing mix models that attribute leads and optimize spend across online and offline marketing channels to deliver $45MM in incremental value- Created lifetime value (LTV) statistical models based on key student attributes to assess channel strategy and product profitability; used to revise pricing scheme at university- Led data scientist team to build ground-breaking statistical forecasting models deployed in a multi-user software platform; provided first-ever integrated views of performance metrics across entire firm- Developed multivariate time-series forecasting models that used online (SEM, Display, Social) and offline (TV, Direct Mail) media spend to predict effect on SEO website traffic- Designed experiments to assess marketing campaigns; recommendations gave 20% lift in response rates- Built tool to measure individual market lift and prioritize $35MM in spend across local markets- Spearheaded marketing ROI dashboard reporting to measure ad-spend efficacy; presented to Board- Constructed cohort-based lead-conversion forecast model to provide student enrollment projections; recognized by senior leadership team as only metrics-based source of long-term company forecast