Analytics & Data Science Working Student contributing to data insights and reporting at 4screen. Collaborating with stakeholders and developing dashboards, reports, and analytical tools for decision - making.
PC
Hybrid Data Scientist – Grid Reliability, Expert
Posted 4 months ago
About the role
- Data Scientist developing advanced data models for electric reliability at PG&E. Collaborating with cross-functional teams to enhance the electric transmission and distribution grid.
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 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.
- 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
- PG&E’s discretionary incentive compensation programs
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