PG&E is looking to develop models to support the Vegetation Management Operational Analytics implementation and operations. This position aims to quantify vegetation risk and develop tools to enable risk-informed operational planning and decision making, ultimately driving down vegetation failures on the system to ensure the safety of customers.
Requirements
- Experience with the following programming languages: PySpark, Python, and SQL
- Experience with Palantir Foundry, AWS SageMaker, and GitHub
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
Responsibilities
- Designs, develops and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes to develop and deploy models quantifying the probability of failure for vegetation in system territory.
- Collaborates with a multi-disciplinary project team of data scientists, data engineers, and subject matter experts on technical development phases: data engineering, analytics/modelling, and visualization/user interface.
- Maintains and enhances data pipelines within the Palantir Foundry platform.
- Applies machine learning and first principles modeling methods to develop robust and reliable analytical models, including visualizations, within the Palantir Foundry & AWS SageMaker platforms.
- Documents data sources, methodology, and model evaluation metrics.
- Serves as the technical lead for development of high complexity models.
- Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
Other
- This position is hybrid. You will work from your remote office and your assigned location based on business needs.
- The headquarters location is flexible within the PG&E service territory.
- Bachelor’s degree in computer science, engineering, applied sciences, mathematics, statistics, econometrics or similar quantitatively focused subject areas or job-related experience
- 8+ years of relevant experience in data science or advanced analytics, OR master’s degree and job-related experience, 6 years, OR Doctorate Degree and job-related experience, 3 years
- Relevant industry (vegetation, forestry) experience, 3 years
- Experience collaborating on a data science team and conducting peer reviews of code and modeling work
- Ability to synthesize complex information into clear insights and translate those insights into decisions and actions
- Ability to clearly communicate complex technical details and insights to colleagues and stakeholders
- Familiarity with Agile product management
- Detail-oriented and meticulous about documentation
