Expert Data Scientist

Requisition ID # 165122 

Job Category: Accounting / Finance 

Job Level: Individual Contributor

Business Unit: Electric Engineering

Work Type: Onsite

Job Location: Oakland

Department Overview

The Electric Planning Policy and Modernization (EPPM) team works collaboratively with diverse stakeholders both within and external to PG&E to streamline and enhance transparency into PG&E’s distribution planning process. EPPM develops new visualization tools, planning tools, and refine processes to inform grid capacity constraints and prepare for building and transportation electrification. The team works in a matrixed environment to identify barriers in delivering electric capacity to our customers and implements solutions to address them. The team also advocates for strategies and policies to integrate DERs effectively and reliably through regulatory proceedings, such as Modernize the Electric Grid for a High Distributed Energy Resources (DER) Future.

The Interconnection Modernization and Analysis (IMA) is part of EPPM organization. The IMA team’s mission is to help our customers and support decision making in a faster and leaner way. We do his by innovation to modernization of the interconnection process, using data and visualization tools, to meet our customer needs.

The IMA team designs and develops state of the art software and tools for distribution planning to integrate load management and DERs in the planning process, automate internal business processes, build visualization tools and maps, and compute highly granular distribution grid capacity data. 
 

Position Summary

The grid capacity data is becoming strategically important as it is used by internal and external PG&E customers to make critical business decisions. The information is used by PG&E customers before they submit a new service application or a new generation interconnection application. IMA team is also designing an IT product based on the grid capacity data to automate the internal processes, that enhance customer’s experience and communications through their new energization requests.
The IMA team is looking for an Expert Data Scientist to support the development of new distribution planning tools based on advanced automated analytics of PG&E’s distribution grid. The Expert Data Scientist designs, develops, and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating actionable insights for strategy and policy development, process improvement, and product enhancement. The individual works on technical development phases: data engineering, analytics/modeling, and visualization/user interface. Interacts with technical and non-technical clients to resolve analysis and technical issues. Works with teams, clients, and senior leadership throughout the development cycle practicing continuous improvement. 

The job responsibilities includes but not limited to developing short-term and long-term plans to enhance the capabilities of the Grid Resource Integration Portal (GRIP), developing data quality metrics, assessing the quality of the input and output data, working with subject matter experts to correct data outliers, working with subject matter experts to regularly publish the fresh data on GRIP, draft reports on the issues, remediation plans, progress, and data quality metrics.

This position is based out of PG&E’s General Office complex in downtown Oakland, CA. 
 
PG&E is providing the salary range that the company in good faith believes it might pay for this position at the time of the job posting. This compensation range is specific to the locality of the job.  The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity.  Although we estimate the successful candidate hired into this role will be placed towards the middle or entry point of the range, the decision will be made on a case-by-case basis related to these factors.
 
A reasonable salary range is:
Bay Area Minimum: $140,000
Bay Area Maximum: $238,000
 

Job Responsibilities

• Acts as peer reviewer of complex models.
• Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
• Presents findings and makes recommendations to high level leaders.
• Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions which create value.
• Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
• Writes and documents reusable python functions and modular python code for data science.
• Wrangles and prepares data as input of machine learning model development and feature engineering.
• Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models which involve multiple facets and iterations in algorithm development.
• Extracts, transforms, and loads data from dissimilar sources from across PG&E for their machine learning feature engineering.
• Creates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets.
• Propose and create system design models, specifications, diagrams, and charts to provide direction to system programmer and development teams.
• Experience incorporating Cybersecurity Principles into Designs such identity-and-access management, Data Encryption, Penetration Testing; and, but limited to Vulnerability Management.
• In depth understanding and project experience, in one or more core business areas of a utility, in the application one or more of the following: Application Architecture, Information Architecture, Data Management, Security, or Infrastructure technologies.
• Familiarity with on-prem and at least one cloud implementation of applications.
• Experience with enterprise business architecture principles and industry standard architecture frameworks.
   

Qualifications

Minimum:

• Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
• 6 years in data science (or no experience, if possess Doctoral Degree or higher, as described above)

Desired:

• Doctoral Degree or higher in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
• Experience in utility and energy industries
• Experience in IT-Information Technology with Leadership Role; in technical implementation experience