Expert Geospatial Data Scientist

1w1 week ago

Pacific Gas and Electric Company

Oakland, US · Full-time · $133,000 – $238,000

About this role

The Data Solutions team in the Wildfire Mitigation organization enhances risk practices for PG&E’s Electric Operation business. It addresses changing external conditions such as climate change by enhancing and maintaining predictive models of electric system failures. These models provide a multi-layered view of risk across the electric system.

This role designs, develops, and executes scripts, programs, models, and algorithms using structured, unstructured, and geospatial data from disparate sources. It generates defensible, valid, scalable, reproducible machine learning and artificial intelligence models for problem solving and strategy development. The position empowers decision-making processes at all company levels.

Day-to-day activities include developing new Machine Learning models to characterize and predict distribution and transmission electric system environmental conditions using remote sensing data. Team members create end-to-end solutions transforming satellite imagery into analysis-ready insights and cloud-optimized datasets accessible in distributed Spark environments. They operate within the Energy Delivery business unit.

The role supports stakeholders in integrating remote-sensing based features into downstream analysis and risk models. It involves participating in internal and external communities of practice in data science, artificial intelligence, and machine learning. Employees educate the non-technical community on advantages, risks, and maturity levels of data science solutions.

Requirements

Expertise in machine learning models using remote sensing and geospatial data
Experience with satellite imagery processing and derived products
Proficiency in developing predictive models for electric system environmental conditions
Knowledge of end-to-end solutions for analysis-ready insights in distributed Spark environments
Ability to handle structured, unstructured data from disparate sources and sizes
Skills in creating scalable, reproducible AI models for risk assessment
Familiarity with wildfire mitigation and electric operations risk practices

Responsibilities

Design, develop, and execute scripts, programs, models, algorithms, and processes using structured, unstructured, and geospatial data
Generate defensible, valid, scalable, reproducible machine learning and artificial intelligence models for problem solving and strategy development
Develop new Machine Learning models characterizing and predicting distribution and transmission electric system environmental conditions using remote sensing data
Develop end-to-end solutions transforming satellite imagery and derived products into analysis-ready insights and cloud-optimized datasets in Spark environments
Support stakeholders in integrating remote-sensing based features into downstream analysis and risk models
Participate in internal and external communities of practice in data science, artificial intelligence, and machine learning
Educate the non-technical community on advantages, risks, and maturity levels of data science solutions