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 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.
Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions that create value.
Act as peer reviewer of complex models.

Requirements

Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
Experience in Data Science, 6 years or no experience, if possess Doctoral Degree or higher in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
Desired: Doctorate degree with 5+ years or Master’s degree with 8+ years in Electrical Engineering, Mechanical Engineering, Operations Research, Transportation Engineering, Physics, Applied Sciences, Statistics, or job-related discipline or equivalent experience
Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
Active participation in professional communities related to utility reliability, such as IEEE Power and Energy Society (PES), is a plus.
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.

Benefits

Eligible to participate in PG&E’s discretionary incentive compensation programs

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data sciencemachine learningartificial intelligencePythonpredictive analyticsreliability analyticsstatistical modelingdata processingadvanced data analysismodeling methodologies

Soft Skills

communication skillsproblem-solvingcoachingteachingcollaborationtechnical leadershipstakeholder engagementtransparencyreproducibilitydefensibility