Lead Data Scientist - Predictive Analytics
PG&E Corporation
- United States
- United States
À propos
# 167320 Job Category:
Accounting / Finance Job Level:
Individual Contributor Business Unit:
Electric Engineering Work Type:
Hybrid Department Overview The System Performance, Reliability and Resiliency Strategy team is passionate about effectively managing resources to execute PG&E's Electric Reliability Strategy successfully. Join our forward-thinking team as we implement innovative technologies and modernize the electric grid for safe and dependable operations. Position Summary As an integral member of the System Performance, Reliability and Resiliency Strategy team, you will report to the Senior Manager of Reliability Analytics. Your expertise in advanced data science models and anomaly detection techniques will play a critical role in enhancing the reliability of our electric transmission and distribution grid. Key Responsibilities: Lead the research and development of pioneering methodologies to identify system failures and enhance grid reliability. Utilize data science, machine learning, and artificial intelligence methods to create scalable and reproducible models. Assume a technical leadership role in the design of predictive and reliability analytics models. Develop efficient Python scripts for data processing and model development, including ML/AI models. Document processes, datasets, and outcomes to ensure transparency and reproducibility. Contribute to data science strategies that align with team objectives. Effectively communicate technical concepts and model findings to stakeholders. Qualifications Minimum: Bachelor's Degree in a relevant field such as Data Science, Machine Learning, or Engineering. 4 years of experience in data science or 2 years with a Master's Degree. Desired: Ph.D. or Master's degree in a related field. Experience in the electric or gas utility, renewable energy, or analytics consulting sectors. Strong foundation in statistics, machine learning, and artificial intelligence. Hands-on experience deploying data science models using Python. Demonstrated ability to address complex, unstructured problems using data-driven methods. Experience working with large datasets, both structured and unstructured. Excellent communication skills for conveying technical ideas to non-technical audiences. A talent for mentoring and coaching aspiring data scientists in AI/ML techniques.
Compétences linguistiques
- English
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