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.
Requirements
- 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.
- Experience designing and operationalizing 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.
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.
Other
- 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.
- 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).
- Doctoral Degree in a quantitative field.
