Architected and implemented modern cloud data solutions for multiple clients enabling them to organize and structure various types of data (subscriptions, billing, social media, viewing) supporting downstream analytics.

Challenge: Joined to rebuild Analytics team in the midst of a pivot from focusing on top-funnel Data Science to more Foundational Business Analytics. Quickly realized that what the organization thought was an Analytics deficit was actually a Data problem. ✦Team Building and Organization- Grew a team of one Data Scientist and Data Strategy contractor into a fully-fledged team with structured focused areas in -BI (Data Visualization, Analytics Engineering) -Data Ops (Data Quality and Architecture) -Insights -Product Experimentation -Partnered with Data Engineering to establish best practices for Warehouse efficiencies ✦Analytics Stack Rebuild-Inherited ungoverned legacy Looker implementation and made BI useable again by -Creating Warehouse Analytics Layer in Snowflake -Moving resource-heavy data modeling and metric building out of LookML using dbt -Shuffling budget by retiring legacy contracts and re-allocating to modern vendors✦Data Quality Process Implementation-Implemented statistically based Certification Strategy to verify consistency of historical data-Developed QA strategy for end-to-end lifecycle of a data point from creation to insight-Implemented data observability using Monte Carlo✦Product Experimentation-Introduced Statistical Rigor to Experimental Design processes

Gave a series of Guest Lectures to a Graduate level class about Cloud Computing.

Taught intensive six-month bootcamp introducing adult students to myriad Anaytical and Data Visualization concepts including Excel, VBA, Git, Statistics, Python (Pandas, Matplotlib), JavaScript (D3, Leaflet), Databases (SQL, NoSQL, Alchemy), API Interactions, Front-End Web Visualization (HTML/CSS), Web Scraping (Beautiful Soup, Tableau, Big Data, Machine Learning, and Cloud ETL (Google Colab, AWS).

Challenge: Joined to help clients maximize the intelligence provided by the Pickaxe BI platform and to provide Data Science insights above and beyond what the core SaaS platform offers.✦Data Science Consulting- Created multiple k-means clustering solutions (including engineering features) to separate BBC streaming subscribers based on how they use the platform and what they watch- Segmented Hayu members to identify which of them are likely to be sharing passwords - Operationalized Data Science products by integrating with CRM and creating trackable widgets in core SaaS product- Produced ad-hoc analytics and strategic recommendations for executive presentations in streaming (BBC/Hayu) and non-profit donation (First Look Media) industries- Built and maintained multiple ETL pipelines for analytics in the cloud using GCP/BigQuery, AWS/S3 and Snowflake.✦SaaS Management- Developed and improved Postgres schemata as business evolution requires new metrics- Served as voice of the customer to develop new widgets, organize dashboards, and proactively QA/squash bugs

Challenge: Joined to modernize, refine and improve AMEX’s marketing platform.Led portfolio-wide CRM transformation initiative, analyzed data to determine product/services usage and profitability and oversaw development of 10+ self-service management reports (BI) supporting Consumer Marketing and Product organizations. Represented AMEX as an invited guest speaker at analytics conferences across the US. Administered technology budget, directed data analytics team and managed ~15 onshore/offshore consultants including programmers, IT developers, and project managers.✦Marketing Transformation/Data Analytics- Transformed AMEX’s “batch and blast” marketing strategy, leveraging data analytics to accurately target messaging and customer communications; resulted in 700% response rate increase.- Built data analytics-centric environment and culture from the ground up; bridged gaps between technology and business units.- Orchestrated migration from legacy (SAS/SQL, Teradata) to modern systems (Hive/Python/Jupyter) and Big Data environment (Hadoop).- Leveraged data simulations to recommend potential commercial partnerships and corresponding product changes.

Challenge: Recruited to build out and lead North American Marketing Testing program and modeling team; promoted to integrate and extend analytics across entire global consumer marketing footprint (Core Products, Retention, Expiring Currency).Drove efforts to segment audiences, devise customer journeys and translate data/marketing reporting into business intelligence. Served as analytical and operational lead on Contact Optimization initiative, oversaw suite of 40+ data-centric marketing models and provided in-depth statistical insights to resolve ad-hoc business issues. Led BI reporting team, statisticians and external vendor relationships. Implemented JIRA for task tracking.✦ Marketing Transformation/Data Analytics:- Played key role in transforming marketing strategy from operations- to Member Lifecycle-focused, improving response rates and revenue by focusing on customer needs.- Established, championed and engrained a data analytics culture, resulting in more collaboration and understanding between teams and full adoption of analytics tools across the entire enterprise.- Implemented data analytics best practices improving marketing outcomes; developed, delivered monthly reporting suite improving overall marketing decision-making.- Spearheaded buildout of logistic predictive, linear Lifetime Value, and Lifestyle Segmentation models used in global Marketing campaigns.✦ Data Testing- Set up rigorous, standardized testing process and formalized data testing structures and governance enabling Marketing to conduct statistically valid tests with unprecedented confidence in the results.- Expanded Testing program globally to all marketing functions and channels (Direct Mail, email, Telemarketing).- Developed global control group strategies and process to effectively measure the isolated effects of individual campaigns and overall marketing strategy.

✦ Played key role in eliminating slow, manual processes by automating SAS and Excel-based BI reporting.

✦ Honed skills in marketing analytics; employed SAS, JMP, SAS EM and Excel to produce and automate marketing reports.

✦ Performed data reporting, credit risk analysis using SAS, SQL, Teradata, and SAS EM tools.