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.
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
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.
Tech Stack
Python
Benefits
This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.