Senior Data Scientist Energy Analytics & ML

PG&E; Oakland (CA); Hybrid; USD 140,000 - 238,000; Full time

Benefits offered by this job

Discretionary incentive program

Job summary

PG&E is seeking a data science professional to design, implement, and validate machine learning models using diverse data sources. The role focuses on predictive analytics and optimization to support wildfire prevention, emergency response, and operational decisions.

The position is hybrid, with a mix of remote work and Oakland-area office presence. Candidates should have deep ML fundamentals, strong Python skills, and experience handling large data sets in energy or utility environments.

Qualifications

• Bachelor's degree in a relevant field (Data Science, CS, Math, Econometrics, etc.).
• 6 years in data science OR Doctorate-equivalent experience as described.

Responsibilities

• Research and apply advanced data science principles to inform business decisions.
• Develop data mining architectures, models, and protocols for structured and unstructured data.
• Extract, transform, and load data from diverse sources for ML feature engineering.
• Develop defensible predictive or optimization models with multiple iterations.
• Prepare data and write reusable Python functions for ML pipelines.
• Assess modeling assumptions, inputs, and methodologies for business impact.
• Present findings to senior management and contribute to model reviews.

Skills

Data science

Python

Machine learning

SQL

Statistics

Education

Bachelor's degree

Tools

TensorFlow

Spark

PyTorch

Job description

PG&E is seeking a data science professional to design, implement, and validate machine learning models using diverse data sources. The role focuses on predictive analytics and optimization to support wildfire prevention, emergency response, and operational decisions.

The position is hybrid, with a mix of remote work and Oakland-area office presence. Candidates should have deep ML fundamentals, strong Python skills, and experience handling large data sets in energy or utility environments.