My core responsibility in this role is to support other analysts in the maintenance and development of quantitative models and to create ad-hoc reports and dashboards for the trading team as requested.
During my time with the The Energy Authority, I've gotten the opportunity to learn and explore the R Shiny web-development platform, the Hadoop and Spark distributed computing grammars, and the obscure corners of the R programming language. The following is a short list of the projects that I've worked on:
- Long-term Stochastics Generational Model
- Simulates generation patterns for various wind and solar farms
- Developed two imputation methods for these models: a copula-fitting statistical method, and a regression method.
- Deployed to production for use in hedge trading.
- Map of renewable energy goals by county
- Key Performance Indicators R Shiny app
- A dashboard of key metrics related to customer portfolios and company forecasts
- Generates presentation-ready PowerPoint with company branding
- Demand forecast for LA County
- Uses hourly demand data for millions of customers in the LA area, necessitating the use of Hadoop and Spark.