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About
The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity.
Although we estimate the successful candidate hired into this role will be placed towards the middle or entry point of the range, the decision will be made on a case-by-case basis related to these factors. Bay Area Minimum: $140,000 Bay Area Mid: $189,000 Bay Area Maximum: $238,000 California Minimum: $133,000 California Mid: $180,000 California Maximum:$226,000 This job is also eligible to participate in PG&E’s discretionary incentive compensation programs. Job Responsibilities Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions. Creates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets Extracts, transforms, and loads data from dissimilar sources from across PG&E Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm development. Writes and documents reusable python functions and modular python code for data science. 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. Presents findings and makes recommendations to senior management. Act as peer reviewer of complex models Qualifications Minimum: Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field 6 years in data science
OR
no experience, if possess Doctoral Degree or higher, as described above Desired: Doctorate Degree in Data Science, Machine Learning, or job-related discipline or equivalent experience Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience Active participation in the external data science/artificial intelligence/machine learning community of practice, as demonstrated through volunteering in professional organizations for the advancement of the field, presentations in conferences or publications to disseminate data science knowledge and topics, or similar activities. Knowledge of industry trends and current issues in job-related area of responsibility as demonstrated through peer reviewed journal publications, conference presentations, open source contributions or similar activities Competency with commonly used data science and/or operations research programming languages, packages, and tools for building data science/machine learning models and algorithms Proficiency in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines. Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders Mastery of the mathematical and statistical fields that underpin data science, specifically focused in reliability and failure analysis Demonstrated proficiency in enterprise data platforms and analytics tools, including Foundry, SAP, and Power BI, with the ability to integrate and analyze data across ERP systems and visualization environments.
Languages
- English
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