Full-Time

Data Scientist – Senior

Grid Reliability

Posted on 12/2/2025

PG&E

PG&E

Compensation Overview

$126k - $179.3k/yr

Oakland, CA, USA

Hybrid

Hybrid role; work from your remote office and an assigned PG&E Service Territory location.

Category
Data & Analytics (1)
Required Skills
Scikit-learn
Python
Data Science
Tensorflow
Keras
Machine Learning
Pandas
NumPy
Data Analysis
Requirements
  • Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
  • 4 years in data science OR 2 years, if possess Master’s Degree, as described above
Responsibilities
  • Lead research and development of state-of-the-art methodologies to detect potential system failures and improve the reliability of the electric transmission and distribution grid.
  • Applies data science/ machine learning /artificial intelligence methods to develop scalable, defensible and reproducible models
  • Serves as the technical lead for the development of predictive/reliability analytics models.
  • Develops python codes for data processing and data science model developments (e.g., ML/AI models, advanced statistical models)
  • Documents datasets, modeling processes, and result to ensure transparency, reproducibility, and defensibility.
  • Contribute to the development of data science strategies aligned with system performance, reliability, and resiliency team goals.
  • Communicate technical concepts and model results to internal/external stakeholders.
Desired Qualifications
  • Ph.D. or Master’s degree in Electrical Engineering, Mechanical Engineering, Operations Research, Transportation Engineering, Physics, Applied Sciences, Statistics, or a related field.
  • Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
  • Strong foundation in statistics, machine learning (ML), and artificial intelligence (AI).
  • Hands-on and theoretical experience in developing and deploying data science and ML models using Python.
  • Proven ability to formulate and solve unstructured, complex problems using data-driven approaches.
  • Proficiency in working with large datasets, including structured and unstructured data from diverse sources.
  • Excellent communication skills, with the ability to explain technical concepts to non-technical audiences.
  • Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies

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INACTIVE