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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** PG&E Corporation - **Location:** Blackhawk, CA, United States - **Experience:** Expert - **Salary:** $126,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Business Analytics Applications, Applicant Tracking Systems, Machine Learning, Software Engineering, Feature Engineering, Model Validation, Information Technology, Data Analytics, Machine Learning Operations, Programming Languages - **Published:** November 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=3f7f1c4aa205131c ## About the Role Minimum 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)., Desired: Master's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field. Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience Demonstrated knowledge of and abilities with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them Competency in software engineering, statistics, and machine learning techniques as they apply to data science deployment Competency in commonly used data science and/or operations research programming languages, packages, and tools Hands-on and theoretical experience of data science/machine learning models and algorithms Ability to synthesize complex information into clear insights and translate those insights into decisions and actions. Demonstrated ability to explain in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines. Competency in the mathematical and statistical fields that underpin data science Mastery in systems thinking and structuring complex problems Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies ## Description The Applied Technology Services (ATS) staff provides advanced analytical, modeling, testing, and risk assessment services across multiple disciplines to support company organizations in identifying, quantifying, and addressing complex operational and asset-related risks. The team develops and applies statistical, probabilistic, and machine learning-based approaches to evaluate system performance, asset condition, degradation trends, and probability of failure, enabling data-driven decision making for reliability, resilience, and lifecycle management. Staff integrate and analyze diverse data sources to develop predictive models, risk metrics, and analytical tools that support asset strategy, maintenance planning, investment prioritization, and operational decision making. Services include asset health assessments, reliability and risk evaluations, failure investigations, scenario analyses, and development of quantitative methodologies for complex infrastructure systems, including transmission and distribution assets, distributed energy resources, and generation facilities. The team provides technical consultation and analytical insights to internal clients, helping organizations proactively manage risk and improve asset performance through the application of advanced modeling techniques, data analytics, and industry best practices. Staff collaborate with business and technical stakeholders to develop analytical solutions, support project proposals, and communicate complex model results and risk insights to decision makers. Incumbents maintain knowledge of and adhere to all company and regulatory safety, quality, and governance requirements. This position is hybrid, working from your remote office and your assigned work location based on business need. The selected candidate must live within PG&E's service territory., probability of failure estimation, and risk quantification to support risk-informed decision making. Develops and maintains probability of failure models, risk metrics, and analytical tools using asset condition, inspection, operational, environmental, and historical performance data to support asset strategy, reliability, maintenance, and lifecycle decisions. Performs model evaluation, sensitivity and scenario analyses, and quantification of uncertainty, and communicates model results, assumptions, failure drivers, and risk insights to engineering, asset management, operational, and business stakeholders.