-Led development on a completely serverless demand planning and space optimization solution. This solution uses custom predictive and optimization models housed in Docker containers orchestrated via Lambda and SageMaker.-Demonstrated the ability to create solutions and tools from abstract business requirements in wide variety of analytics disciplines: predictive analytics, demand forecasting, recommender algorithms, and Natural Language Processing.-Mentored junior analysts and taught them best practices on predictive modeling, Docker, agile development and the AWS cloud.

- Implemented a machine learning style algorithm that drastically improved occupancy forecasting for Delaware North’s Park Services. This included mining and transforming complex time series data. - Created a dynamic dashboard for tracking and analyzing resort performance using SAS Visual Analytics, including writing the SQL code that dynamically creates the data sets for the report.  Developed multiple algorithms in Python that structure unstructured financial data for each of Delaware North’s NFL subsidiaries.

-Accomplished market research using advanced data scraping techniques: html scraping using Python and the Beautifulsoup package and automated data extraction of tax form 990 files with a bespoke Python program. - Successfully performed a full financial sensitivity analysis of future operational decisions using excel and presented the analysis directly to the Board of Directors of the project. - Created a comprehensive modeling tool in Excel for the key stakeholders to perform ad hoc analysis of operational decisions. Using data tables and linear programming macros, this tool allowed users to manually adjust a series of inputs and analyze the impact of their decisions on the 10-Year NPV while also giving the user a dynamically generated budget and marginal revenue targets to achieve positive NPV.

-Created new reporting procedures in Microsoft Excel that gained immediate executive visibility and put renewed focus on a particular operational opportunity.-Forecasted loan volume using ARIMA regression techniques in Python and visualized that data in concise, easily interpretable reports for leadership. -Mined, munged, scrubbed, and analyzed data sets. Analysis included decomposing yearly, monthly, and seasonal trends, regression testing, correlation and covariance analysis, and data visualization. -Invited to present my analysis to senior leadership with a presentation based on “Presentation Zen” principles.

• Led 63 employees and reduced employee turnover 10% over my predecessor by re-evaluating all employee availabilities and personally handling recruiting responsibilities. • Reorganized our server workflow and station design, raising our measured attentiveness of server by 11% in Q1 2015 while also lowering our overall percent of comp food from 1.1% to .84% in the same quarter.• Two of my direct hires were chosen by leadership to open restaurants in both the United States and Mexico because of their extraordinary fit for their position.• Recognized as the Manager of the Quarter for my restaurant 5 times during my tenure due to my unwavering commitment to both our guests and our staff.

• Managed more than 20 employees, including line cooks, prep staff, dishwashers and stewards.• Forecasted and directly managed a culinary operations budget in excess of $200,000 monthly.• Managed vendor relations and successfully reduced produce cost by 3% by adding an additional vendor to the restaurant and re-organizing our internal order sheet bi-weekly with updated prices.• Scored in the top 10 % among all restaurants in internal food safety audit by implementing a new hourly staff accountability program in the restaurant• Managed the hiring cycle for all new culinary hires, including recruiting, on-boarding, and on the job training.