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Expert Data Scientist (Flexible Location)
  • Python
  • Spark
  • SQL
  • Machine Learning
  • Tableau
  • Database
  • Data Visualization
  • Modeling
San Francisco, CA 94105
132 days ago

Requisition ID # 30062

Job Category : Accounting / Finance

Job Level : Individual Contributor

Business Unit: Electric Operations

Job Location : San Francisco

Department Overview
The aim of the Risk Analytics team is to enhance the risk practices of PG&E’s Electric Operation business and thereby address changing external conditions such as climate change. To this end the Risk Analytics team creates and maintains tools to enable PG&E to close the gap between metrics and electric system performance. These tools provide a multi-layered view of risk across the electric system so that decision-making processes include and empower employees at all levels of the company to manage risk appropriately.

In creating these tools, the team employs a data supported, lean solution process to expand PG&E’s ability to assess and manage risk. The result are assessments and mitigations that are more dynamic, quantitative, and customer-focused, with a multi-layered approach for both short-term and long-term time horizons.

Sample activities include:

  • Interpretation and representation of meteorological data in models that combine a range data sources such as the electric system asset data, vegetation and meteorology
  • Development of computer vision models aimed at accelerating and automating asset inspections processes
  • Predicting electric distribution equipment failure before it occurs allowing for proactive maintenance
  • Supervised and unsupervised machine learning models using Python and Spark, executed on AWS

Position Summary
We are looking for an Expert Data Scientist to join our growing team. In this role you will have a unique opportunity to be at the forefront of utility industry analytics and their use in tools to asses risk. Working as part of cross functional team, including other data scientists, technology experts, and subject matter experts this individual will help develop data driven solutions for decision making and operations. It is the perfect role for someone who would like to continue to build upon their professional experience and gain a comprehensive view of the nation’s most advance smart grid.

Job Responsibilities

Analytics and Modeling

  • Gather, prepare, and analyze data from disparate sources to produce user-friendly models and actionable insights
  • Understand and appropriately apply statistical and analytical modeling methods such as classification, regression, clustering, anomaly detection, neural networks, etc. to identify opportunities for operational improvements and develop strategic insights
  • Work collaboratively with other data scientist through an iterative Agile project development lifecycle

Communication, Summary Presentation, and User Interfaces

  • Appropriately document data sources, methodology, and model evaluation metrics
  • Develop and present summary presentations to management
  • Create streamlined visuals, and tools for end-users


  • Degree in computer science, engineering, applied sciences, mathematics, statistics, econometrics or similar quantitatively focused subject areas or job-related experience
  • Minimum of 8 years of relevant experience in data science or advanced analytics OR Master’s Degree and job-related experience, 6 years, OR Doctorate and job-related experience, 3 years


  • Strong oral and written communication skills
  • Demonstrated collaboration or paired development work history
  • Demonstrated proficiency with relational databases, preferably in SQL
  • Demonstrated proficiency with data science best practices, such as version control via Git or similar
  • Demonstrated proficiency with model development for decision analysis, forecasting, or other complex quantitative modeling
  • Demonstrated experience writing clear and well documented code, preferably in Python
  • Demonstrated experience working with large datasets and knowledgeable about parallelization
  • Strong understanding of statistics and experience developing supervised & unsupervised learning models

Beneficial Qualifications:

  • History mentoring and teaching others as well as desire to continue to do so
  • Demonstrated experience with data visualization tools such as Tableau, D3, Plotly, etc.
  • Enjoy working on complex multi-stage projects with a diverse team
  • Involvement or strong interest in the energy/clean tech industry
  • Familiarity with transmission and/or distribution power flow models
  • Past experience with advanced metering interval data

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