Resume

• 2005

  Masters of Arts

  Economics

• 1998

  Bachelor of Arts (BA)

  Business/Economics

  UC Santa Barbara

• Data Analysis

  SAS programming

  Microsoft Excel

  Forecasting

  Analytics

  Energy

  Electricity Markets

  SAS

  Cost Benefit

  Qualitative Research

  access

  Econometrics

  Statistical Data Analysis

  Energy Efficiency

  Analysis

  Access

  Statistics

  Economics

  Energy Industry

  Javanbakht

  Reliant Energy

  California ISO

  Sperian Energy

  San Diego State University

  Cuyamaca Community College

  Itron

  Pacific Gas and Electric Company

  Teach a class of 220 students the principles of Macroeconomics using up to date information about the economy. Teach intro statistical methods by applying real word data and methods to assist students in learning real world statistical tools and analysis. Concepts range from the basics of quantitative vs. qualitative

  standard deviation

  confidence interval to multiple regression analysis.

  San Diego State University

  Sperian Energy

  Reduced production time by 400% and increased accuracy in the broker tracking and payment system. Moved from manual entries to automated databases.\n\nRedesigned the sales reporting process and analysis. Created in depth analysis all key sales figures. Showed trends based on time frame

  location and source.\n\nResponsible for quality assurance in enrollment of new customers into service and existing 40

  000 enrollments. \n\nImplemented first step in compliance based on JPM territory based on state specific PUC requirements. \n\nAssisted the Customer Service Representatives in data verification and inquiries. \n\nLead analyst in load forecasting.

  Energy Analyst

  Greater San Diego Area

  San Francisco Bay Area

  Implement a new gas load forecasting platform

  streamline the process of creating reports

  and increase model accuracy. Move from a spreadsheet and E-views forecasting process to solely SAS and database structured process.\nModeling: Revamp current models to reflect more of the trends and characteristics of the customer class within PG&E territory. This includes

  but is not limited to

  a more accurate responsiveness to weather and gas rates

  drought potential

  energy efficiency

  industry specific economic activity

  and seasonality.\nForecasts: Produce statistically sound and valid monthly forecasted values that reflect the current state of the PG&E service territory out to 2030. Defend forecast to Senior Vice President and Directors prior to being published. \nIndustrial Price Accuracy: Work with a team of experts at PG&E and with the California Air Resource Board (ARB) to calculate GHG prices that industrial gas customers are facing using only publicly available information for internal forecasting as well as in rate cases. Our team is the first in the nation to undertake this process.\nWeather Data Improvement: Document the previous HDD and CDD weather calculation process and propose the current method continuously update HDD and CDD. In coordination with one of the company’s meteorologists

  create new historical weather data and incorporate global climate change impacts on CDD and HDD for the twenty-year weather forecast period.\nQA/QC: Address data inconsistencies from different data sources that had been present for six years. Update interpolations of economic data to more accurately reflect reporting periods. Leveraged interval metered data to create more accurate calendar data from billing data

  Expert Load Forecasting Analyst - Consultant

  Pacific Gas and Electric Company

  Analyst in the northeast market

  PJM

  NYISO and NEISO territories

  in developing the framework for the forecasting team. \n\nCreate models for each load profile in the Reliant Northeast market. All profiles

  which includes but not limited to large commercial

  small commercial/business

  residential non-heating and residential heating

  are treated differently by incorporating distinct weather variables for that region and calendar variables for the specific sector. Included an AR1 process in the econometric model for increased accuracy.\n\nCalculate forecasted energy values for profiles in each territory using typical meteorological year normal weather values. Using SAS the values are incorporated for other departments including supply

  risk and marketing. \n\nResearch market trends on the possible impact demand for the region and utility. Find documentation on each utility and ISO about their approach to load forecasting including the variables used

  specifics of each rate class and the demographics that make up the profile.

  Senior Load Forecasting Analyst

  Houston

  Texas Area

  Reliant Energy

  Applied statistical methods

  mathematical and economic principles to collection

  analysis

  and presentation of data. Uploaded and cleansed data from various resources into a usable database. Drafted sections of project reports.\n\nCalculated cost effectiveness of utility Energy Efficiency programs using Total Resource Cost. \n\nLed analysis for multifamily efficiency program in a reduced time frame. Finished all tasks on schedule including collecting and cleaning of tracking data

  directing telephone surveyors

  authoring impact analysis and final report writing. \n\nDeveloped regression model to forecast energy usage using MextrixND forecasting software based on 20 years of hourly weather data

  holidays

  and days of week. Model was used to predict load structures for Oklahoma Gas and Electric. \n\nConducted various statistical analyses on variables such as verified energy savings

  net to gross calculations and precision levels in the We Energies Energy Efficiency Procurement Program.

  Energy Analyst II

  Greater San Diego Area

  Itron

  Taught all the economic classes which include Principles of Macroeconomics

  Principles of Microeconomics and Economic Issues and Policies. Classes also include condensed semester classes which are 8 weeks long and summer session as well. Class sizes range from 20-70 students in a class. An advantage of small class sizes is that I can run ‘simulations

  ’ which consists of students enacting economic concepts. This method is applied to each one of three different classes.

  Cuyamaca Community College

  California ISO

  Folsom

  CA

  Create all CAISO load models to be used in the market and advisory forecasts using machine learning methods. \nPlayed a lead role in the restructure of how the market receives load forecasts to assist with congestion. This was one of the biggest changes to how CAISO produces a forecast. This was worked with OEs to optimize their needs with the best load response to weather.\nLead the incorporation of accurately tracking DER impacts on the grid to assist real time and day ahead load forecasts. \nAsses COVID-19 impacts on the grid to determine how the grid has been impacted and develop solutions to address the issues. \nInterim Manager during 2019 summer.

  Lead Model Forecast Analyst

  Persian