Principal, Data Scientist

Requisition ID # 167305

Job Category: Accounting / Finance

Job Level: Manager/Principal

Business Unit: Operations - Other

Work Type: Hybrid

Job Location: Oakland

Position Summary

PG&E is seeking a Principal Data Scientist to lead the development and deployment of advanced analytics and machine learning solutions that support vegetation management operations, regulatory compliance, and wildfire risk mitigation. The Principal Data Scientist will design and operationalize predictive and optimization models using structured, semi-structured, and unstructured data—including remote sensing imagery (LiDAR, orthoimagery, surface reflectance), geospatial datasets, and operational data from platforms such as Salesforce (OneVM), SAP, SharePoint, and ArcGIS. The ideal candidate will bring deep technical expertise, strategic vision, and leadership to drive data science maturity across Vegetation Management.

This position is hybrid. You will work from your remote office and your assigned location based on business needs. The headquarters is the Oakland General Office.

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, collective bargaining agreements, and internal equity.

A reasonable salary range is:

- Bay Area Minimum: $159,000

- Bay Area Maximum: $271,000

AND/OR

- California Minimum: $151,000

- California Maximum: $257,000

This job is also eligible for participation in PG&E’s discretionary incentive compensation programs.

Job Responsibilities

- Develop and deploy machine learning and optimization models to support vegetation risk assessment, work prioritization, and regulatory reporting.

- Integrate and analyze diverse datasets including geospatial imagery, sensor data, and operational records to uncover actionable insights.

- Collaborate with data engineers to ensure robust feature pipelines and model deployment workflows using platforms such as Snowflake, Informatica, SageMaker, Foundry, or custom AWS-based solutions.

- Apply and evaluate advanced statistical, machine learning, and AI techniques to build scalable, reproducible, and defensible models.

- Write modular, reusable Python code and contribute to shared libraries for vegetation analytics.

- Mentor junior data scientists and foster a culture of innovation, reproducibility, and ethical AI use.

- Partner with business stakeholders, regulatory teams, and field operations to translate complex data science outputs into strategic decisions.

- Present findings and recommendations to executive leadership and cross-functional teams.

- Advocate for data-driven transformation across Vegetation Management and contribute to PG&E’s enterprise data science community.

Qualifications

Minimum:

- Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Engineering, Mathematics, Statistics, or a related technical field.

- 8 years of experience in data science (or 2 years with a Doctoral Degree).

- Proven experience developing and deploying machine learning models in production environments.

- Proficiency in Python and SQL, with experience in distributed computing frameworks (e.g., Spark).

- Experience working with cloud platforms (preferably AWS and Snowflake) and data lakehouse architectures.

- Strong understanding of software engineering best practices including CI/CD, version control, and testing.

Desired:

- Doctoral Degree in a quantitative field.

- Familiarity with vegetation management, wildfire risk modeling, or utility operations.