Job Location: Oakland, CA
Job Location: Oakland
Team Overview
PG&E’s Strategic Wildfire Intelligence Management (SWIM) team within the Wildfire Risk organization manages the integrated and foundational data pipelines that support development & utilization of Risk Models, Work Plans, Operational Reporting, and front-end Applications for Special Programs. As part of this work, this team partners closely with data analytics teams and PG&E’s IT organization to enable delivery of meaningful insights that shape the company’s trajectory each year and achieve our stand that “ Catastrophic Wildfires Shall Stop ”.
SWIM aligns and maintains a strong influence to company-wide best practices for data management, modeling, analytics, and data science. We are early adopters to the Lean Operating System’s Daily, Weekly, and Monthly Operating Reviews – as well as 1-3-10 Visual Management. Our call to action is to use data to shine a light to help teams and leadership “see” through the noise, enabling data-driven decisions that leverage an authoritative, single-source of truth.
Sample activities include:
New data pipelines and ontology that combine a range of data sources such as the electric system asset data, work management activities, and meteorology insights
Reporting dashboard development that includes both geographic and tabular insights
Common Operating Picture – continuous evolution of a 360-degree, real-time view into PG&E’s expansive portfolio of critical Wildfire Mitigation workstreams such as EVM, System Hardening, and the EPSS programs
Ad-hoc data coding and analysis using SQL, Pyspark, and Palantir Foundry’s Contour / Code Workbook applications.
Machine learning model development using Palantir Foundry’s ML Library & Toolkits
Position Summary
We are looking for a Senior Data Scientist to join our growing team. In this role you will have a unique opportunity to be at the forefront of utility industry data management and contribute to the ever-critical integrity of our data assets. 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.
This position offers a flexible location within the San Francisco Bay Area. Reporting to our Oakland General Office will be required once a week.
Responsibilities:
Analytics and Modeling
Gather, prepare, and analyze data from disparate sources to produce user-friendly models and actionable insights
Work closely with domain experts. Develop a working knowledge of utility data structures and elements
Develop expertise with grid data, customer demographic information and other structured data sets
Understand and 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
Communication, Summary Presentation and Visualization
Appropriately document data sources, methodology, and model evaluation metrics
Develop and present summary presentations for senior management
Create streamlined visual tools for end-users
Work with business partners to advance business processes, based on analytical findings
Work with team leadership to continually improve analytics at PG&E via demonstrations, mentoring, disseminating best practices, etc.
Qualifications
Minimum:
Degree in computer science, engineering, applied sciences, mathematics, statistics, econometrics or similar quantitatively focused subject areas or job-related experience
Minimum of 5 years of relevant experience in data science or advanced analytics OR Master’s Degree and job-related experience, 3 years, OR Doctorate and job-related experience, 5 years
Knowledge of Microsoft Office Products – for example Teams, Excel, Word, Power BI, PowerPoint, Access
Desired:
Demonstrated collaboration or paired development work history
Demonstrated proficiency and experience working with relational databases, preferably in SQL
Demonstrated proficiency writing clear and well documented code, preferably in Python
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 e xperience working with large datasets and knowledgeable about parallelization
Strong understanding of statistics and experience developing supervised & unsupervised learning models
Knowledge of database and information systems – for example SCADA, EMS, OMT, OIS, SAP, GIS
Beneficial Qualifications:
Enjoy working on complex multi-stage projects with a diverse team
Involvement or strong interest in the energy/clean tech infrastructure
History mentoring and teaching others
Familiarity with transmission and/or distribution power flow models
Past experience with advanced metering interval data
Demonstrated experience with data visualization tools such as Palantir Foundry, Tableau, or PowerBI
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