• Member of a team doing feature development work across four codebases that underlie the GX Cloud SaaS application.• Led the effort to integrate with and surface the core product abstraction (44 Expectations) to users of GX Cloud.• Acted as lead on 8 epics to adapt open-source features for Cloud or build new differentiated capabilities for the application.• Involved in a tiger team initiative that open-sourced an internal JSON schema TypeScript form rendering library.• Led 33 technical and team interviews to support hiring decisions during a period of rapid engineering team growth.• Implemented contract tests for API changes between systems, ensuring stable integrations and reliability across updates.• Built end-to-end integration tests for API workflows, reducing regression risks between the Python API and the REST API.• Developed analytics to track and measure user engagement with new features and tools.

• Core developer of the most widely used data quality framework for modern data engineering workflows.• Created interactive data profiling charts, enhancing data exploration for suggested tests to improve data quality.• Spearheaded a new rendering API to visualize data quality test results across multiple front-end environments.• Participated in 14 team interviews, assessing technical skills and cultural fit to support team growth and hiring goals.• Incrementally added static type safety, reducing technical debt and improving maintainability of the codebase.• Streamlined test efficiency by caching dependencies in containerized builds, cutting CI/CD times.• Developed bootstrap and kernel density estimation (KDE) methods for flexible data range estimates in the profiling API.

• Acted as Product Owner and Developer on both the back-end and front-end of 2 production Tableau scorecards• Integrated the data quality framework Great Expectations into our pipeline by contributing the first open source Oracle commits• Implemented Apache Airflow and Git version control in a Docker container for automation of the team’s ETL and ML workflow• Prototyped a CNN classifier using TensorFlow / Keras to predict latent processes associated with data submitted by 3rd parties• Leveraged Facebook’s Prophet library for time series forecasting of order volumes and visualized the forecast with Matplotlib• Identified influential variables for users of a scorecard that were performing RCA, utilizing scikit-learn’s random forest classifier

• Wrote a browser-based model interpreter in D3.js to communicate to stakeholders the rationale for model decisions• Communicated the story to stakeholders in presentations via visualization of logistics data distributions in R using ggplot2• Fit models using R to predict the presence and condition of timestamp data using various independent supply chain variables• Built an Oracle data warehouse for the business intelligence team to utilize for KPI reporting and lead time segmentation

• Planned distribution, placed purchase orders, and tracked supply chain milestones, for over $150MM of inventory annually• Forecasted product demand at 8,000+ stores for 500+ items using historical data, external factors, and 3rd party machine learning• Queried Hadoop or databases directly via SQL daily for forecasting, system parameter tuning, distribution planning, and reporting• Guided the sales and operations planning process through optimization modeling and tracking plan execution