Data Scientist in PG&E's Reliability Analytics, developing advanced data science models for grid reliability. Collaborating with cross-functional teams on innovative methodologies.
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).
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.
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.
Benefits
PG&E is providing the salary range that can reasonably be expected for this position at the time of the job posting
This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.
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