Principal Data Scientist

Job Summary

The Undergrounding Risk Management team within the Undergrounding & System Hardening organization enhances risk practices for the Electric Operation business, addressing external conditions like climate change. The Electric Risk Management & Analytics team develops predictive models to improve electric system performance.

Key Responsibilities

• Researches and applies advanced data science principles to inform business decisions.
• Develops data mining architectures, statistical reporting, and data analysis methodologies to identify trends in data sets.
• Extracts, transforms, and loads data from various sources for machine learning feature engineering.
• Applies data science and machine learning methods to develop predictive or optimization models involving multiple facets and iterations in algorithm development.
• Wrangles and prepares data for machine learning model development and feature engineering.
• Architects, develops, and documents reusable functions and modular code for data science.
• Affirms business implications related to modeling assumptions, inputs, methodologies, technical implementation, analytic procedures, and advanced data analysis.
• Works with stakeholder departments and company subject matter experts to understand and apply data science solutions.
• Presents findings and makes recommendations to senior management.
• Acts as a peer reviewer of complex models.

Required Skills

• PySpark proficiency
• User interface development proficiency
• Strong cross-functional collaboration skills

Preferred Skills

• Expertise in experimental design and causal inference methods
• Expertise in statistical methods for time series analysis, statistical modeling, and probabilistic risk assessment
• Relevant industry experience (electric or gas utility, data science consulting, etc.)
• Familiarity with supervised, unsupervised, deep learning & physics-based methods for modeling electrical infrastructure failure modes
• Competence with data science standards and processes (model evaluation, optimization, feature engineering, etc.)
• 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
• Proficiency with Agile product development best practices
• Proficiency in explaining technical concepts including statistical inference, machine learning algorithms, software engineering, and model deployment pipelines
• Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders
• Ability to develop, coach, teach, and/or mentor others

Education Requirements

• Required: Master's Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field
• Preferred: Doctorate Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field

Experience Requirements

• 8 years of experience in Data Science; OR 2 years of experience if possessing a Doctoral Degree or higher in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field

About the Client

This client is a major utility and energy company delivering natural gas and electric power to approximately 16 million people across a 70,000-square-mile service area spanning northern and central California. They operate some of the most complex energy infrastructure in the country, including transmission lines, pipelines, substations, and generation facilities. Professionals across data science, engineering, technology, and operations work here to advance reliable, safe energy delivery while driving the organization's digital and clean energy transformation.

About GTT

GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.