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Manager of Marketing & Student Recruitment directing recruitment strategies for graduate programs. Collaborating with faculty and prospective students while leveraging marketing strategies.
PC
Hybrid Senior Data Scientist – Predictive Analytics
Posted 3 days ago
About the role
- Leads development of advanced data science models to enhance reliability of electric transmission and distribution grids for PG&E. Involves cross-functional collaboration and participation in industry advancements.
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
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
- 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.
Benefits
- PG&E’s discretionary incentive compensation programs
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