Senior Data Scientist

Position Summary

The Senior Data Scientist will advance analytics, machine learning, and Generative AI solutions that improve customer experience and deliver measurable business value. Using structured and unstructured data, including customer feedback, interactions and operational datasets you will uncover insights that support Call Hours, Customer Transaction Score (CTS), Escalations, Overall Satisfaction (OSAT), and other key customer experience priorities.

This role offers the opportunity to work on high impact projects that shape customer strategy, inform policy, optimize processes, and improve products and services. You will develop scalable data science and AI solutions, including predictive models, GenAI-powered tools, chatbots, and other AI-enabled capabilities that help coworkers work more efficiently and deliver better customer outcomes.

You will be part of a team that is actively exploring and deploying cutting edge AI solutions to transform how we serve our hometowns and create value for customers, coworkers, and the business.

This is a hybrid position, with work performed from your remote office and assigned work location based on business needs and company requirements.

Compensation

PG&E is providing the full salary/pay range for this position. The actual amount 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 range to reasonably expect will be around the minimum and the midpoint <$126,000 - $163,000>. The final decision will be made on a case-by-case basis related to the factors above.

This position is also eligible to participate in PG&E’s discretionary incentive compensation programs. PG&E offers a comprehensive benefits package that includes medical, dental, and vision coverage, a 401(k) retirement savings plan, paid time off, and other benefits and programs available to eligible employees.

Bay Area Min: $ 126,000

Bay Area Mid: $ 163,000

Bay Area Max: $ 200,000

Job Responsibilities

• Lead the design and delivery of machine learning, statistical modeling, and Generative AI solutions that solve high value business problems and improve customer experience.
• Translate large, complex structured and unstructured datasets into actionable insights, strategic recommendations, and measurable opportunities
• Build, deploy, and continuously improve predictive models, AI applications, and automated data pipelines that scale across the business.
• Design and evaluate experiments, including A/B tests to measure business impact and guide decision making
• Partner closely with business stakeholders, channel teams, and domain experts to identify opportunities and drive data informed decisions
• Communicate complex analytical findings through compelling storytelling, clear documentation, intuitive visualizations, and executive ready presentations.
• Develop deep expertise in customer, billing, operational, and survey data to uncover drivers of performance and support long term strategic planning
• Stay current with advances in data science, machine learning, and AI, and translate relevant innovations into practical business applications.

Qualifications

Minimum:

• Bachelor’s degree in computer science, data science, statistics or job-related discipline or equivalent experience
• Job-related experience, 5 years, OR Masters Degree and job-related experience, 3 years, OR Doctorate Degree
• Experience with Python, SQL
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks)

Desired

• Graduate Degree in job-related discipline or equivalent experience
• Utility industry experience, 1-year
• Customer analytics, 1-year
• Experience with Teradata and Oracle
• Experience with Power BI
• Experience in applying Gen AI to solve business challenges
• Experience with the automation of machine learning, and Gen AI pipelines
• Ability to synthesize complex information into clear insights and translate those insights into decisions and actions
• Ability to clearly communicate complex technical details and insights to colleagues and stakeholders