Artificial intelligence Jobs in Berkeley, CA

Position Summary

Within the System Performance, Reliability and Resiliency Strategy team, this position reports to the Senior Manager of Reliability Analytics and is responsible for developing advanced data science models and industry-leading anomaly detection techniques to identify potential failures and enhance the reliability of the electric transmission and distribution grid.

Key responsibilities include designing, developing, and executing scripts, programs, models, algorithms, and processes using structured and unstructured data from diverse sources and of varying sizes. The goal is to generate defensible, valid, scalable, reproducible, and well-documented machine learning and artificial intelligence models (predictive or optimization) to support problem-solving and strategic decision-making.

The role also involves active participation in internal and external communities of practice in data science, AI, and machine learning to stay current and contribute to advancements in the field. Additionally, the candidate will help educate non-technical stakeholders on the benefits, limitations, and maturity of data science solutions.

In this role, the successful candidate will be uniquely positioned at the forefront of utility industry analytics. Working as part of cross-functional teams, including data engineers, data scientists, technologists, and subject matter experts – this individual will lead the development of data science capabilities that could lead to paradigm changes in how the utility operates.

• This position is hybrid, working from your remote office and your assigned work location based on business need. The assigned work location will be within the PG&E Service Territory.

PG&E is providing the salary range that can reasonably be expected for this position at the time of the job posting. This salary range is specific to the locality of the job. The actual salary paid to an individual will be based on multiple factors, including, but not limited to, internal equity, specific skills, education, licenses or certifications, experience, market value, and geographic location. The decision will be made on a case-by-case basis related to these factors. This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.

Bay Area - $126,000 - 179,300

&/OR

California: $120,000 - 170,500

Job 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.

Qualifications

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:

• 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