Eric Sebring Email & Phone Number

San Diego, California, Us

• Built and maintained an AWS database, utilizing AWS EventBridge and Lambda to schedule and run Python code to ETL data from a CAISO HTTP API. Data was then stored in a MySQL RDS table where it could be extracted by end users. o Lambda was supported by native Pandas SDKs and custom layers imported via ZIP file.o VPC’s, security groups, subnets and routing tables were all customized for security.o End result: end users had access to historic datasets and had access to the most up-to-date data, saving considerable time.• Built and implemented a local Python application that utilized a third party API to ingest and synthesize market data to reduce risk, improve business operation and improve department efficiency. A user interface, utilizing tkinter, was created for ease of use for stakeholders.• Coordinated with devops and data engineering teams to ensure proper data quality for applications and APIs used by third parties. • Developed models to optimize battery bidding strategy and identify best/worst contract profitability.• Built 10+ Power BI dashboards to visualize key department metric and KPIs to run the business more efficiently. • Reviewing and responding to CAISO energy trading settlement statements and disputes• Utilizing visualization tools to respond to data requests and building analytical efficiencies• Liaising between third party CAISO data and policy providers• Advising on trading strategies to minimize settlement disputes

San Diego, Ca, Us

• Developed and maintained a data ecosystem in which stakeholders can access insightful metrics and prepackaged reports to assess their business units.• Automated monthly tracking of new product KPI’s into a Power BI dashboard that refreshes daily, using Python and SQL, increasing efficiencies and availability of key metrics.• Developed new KPI’s to track asset performance and created a prescriptive algorithm to allocate the assets optimally. Metrics enabled the ability to pinpoint underperforming assets and informed key stakeholders to take prescriptive actions to optimize revenue.• Integrated third party healthcare claims data with internal data to enhance marketing strategies, producing increased revenue on undiscovered clientele.• Mentored multiple individuals who were interested in Python, SQL, and Power BI and provided a roadmap to accomplish similar projects. These individuals were not new hires and were interested after seeing the success I was achieving.• Oversaw administrative access to all dashboards, consisting of permissions, access and row level security which prevented teams without access to certain data to see such KPI’s and metrics.

San Diego, California, Us

• Improved an existing python analysis program by creating: a user-friendly interface, an executable file for ease of use, a user interface for the installer of the executable and program dependencies, real time version control, and automatic PDF’s.• Increased efficiency of program by 3000% and enabled accessibility to the program from a single python developer to a department of 10 people. • The analysis, created by the program, is provided to influential California intervenors in legal proceedings governed by the California Public Utilities Commission (CPUC).• Improved existing VBA macros to ensure all programs are working as designed.• Ensured all electric rate changes for SDG&E are carried out in accordance with the proper CPUC & FERC authority and properly recovered revenues through the proper channels.• Created executive level presentations to provide key insights into past, present and future rate and revenue impacts as well as analyzed key factors for management into upward rate pressures.

San Diego, California, Us

• Designed and integrated a customizable dashboard which provided gas analysis reports for incoming rate changes. Such reports were utilized by the top 3000 customers in order to forecast costs associated with gas bills.• Dashboard utilized a Python-based UI compiled by Pyinstaller and designed in Tkinter that utilized the Pandas/PyODBC libraries to execute SQL queries to import data and manipulate time-series data based on selections made on the UI (ETL).• Formatted output and visualizations by XlsxWriter to ensure standard output across multiple reporting tools.• Utilized Pandas and Numpy to calculate complex bill estimations based on rate, rate set, and date range to output a custom analysis for the given account, including considerations of tax status, city taxes and applicable riders.• Developed a cache is created by inserting all pertinent information into a SQL table for reporting, user tracking and debugging.

San Diego, Ca, Us

• Improved process efficiencies by 20 hours per week by implementing a Python-based program that schedules reoccurring, daily reports to be sent to various departments to ensure proper management of accounts undergoing conversions.• The program utilizes the Schedule library to execute specific functions, combined with PyODBC/Pandas/Numpy to gather, cleanse and manipulate the data based on the specific report needed. Scheduled reports are sent with Win32com.client through Outlook, with a prepared HTML format to ensure email consistency.

Bachelor Of Arts - Ba, Economics

Master Of Business Administration - Mba

Education record