Forecasting at Hinge Health has evolved over the past four years from a spreadsheet-based Finance calculation to a production-caliber system using various R packages such as targets and fable for time series forecasting. This presentation will tell the story of forecasting at a digital healthcare tech startup and highlight learnings from the journey. In particular, we will discuss the statistical modeling process, forecast accuracy and variance analytics, getting buy-in from stakeholders for a new forecast framework, integrating forecast models’ input and output with the existing data model, and solutions to move statistical models and forecasts from a local machine to a production environment.
Agenda
- 5:30PM Pizza and Networking
- 6:00PM Presentation
Speaker Bio
Laura Darby Rose is a Senior Staff Data Scientist at Hinge Health, where she is accountable for building and maintaining forecasting models. Her previous experience includes pharmaceutical, economic consulting, and food manufacturing companies. Laura is passionate about using open source technologies such as R and Python to design forecasting solutions. She earned CPF (Certified Professional Forecaster) and CPIM (Certified in Planning and Inventory Management) certifications from the Institute of Business Forecasting and Association for Supply Chain Management, and has presented on time series forecasting for FASTCon, Open Source Quantitative Finance Conference, R Ladies St. Louis and R in Supply Chain meetups. Laura is a co-organizer for the R Ladies St. Louis chapter and enjoys promoting gender diversity in the data science community. She holds a Master’s degree in Economics from the University of Missouri-St. Louis, and has over 10 years of experience in forecasting and demand planning.
