Data Scientist

Requisition ID # 164712

Job Category: Accounting / Finance

Job Level: Individual Contributor

Business Unit: Electric Engineering

Work Type: Hybrid

Job Location: Oakland

Department Overview

The System Performance, Reliability and Resiliency Strategy team within the overall Electric Transmission and Distribution Engineering organization is responsible for planning, organizing, and managing the resources necessary to successfully execute PG&E’s Electric Reliability Strategy and initiatives. This team of forward–thinking individuals will be tasked with deploying technology and infrastructure and influencing the organization to achieve the company’s reliability goals. The team is responsible for implementing programs required to modernize the electric grid allowing for safe, resilient and efficient operations. The team participates in a cross functional team of internal and consulting participants being tasked with leading the transition of a project from development and testing to being operational for each phase of each project.

• 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 the company in good faith believes it might pay for this position at the time of the job posting. This compensation 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, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity. Although we estimate the successful candidate hired into this role will be placed towards the middle or entry point of the range, the decision will be made on a case-by-case basis related to these factors.

Bay Minimum: $102,000

Bay Maximum: $162,000

&/OR

CA Minimum: $97,000

CA Maximum: $154,000

This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.

Position Summary

Within the System Performance, Reliability and Resiliency Strategy team, this position reports to the Sr Manage, Predictive Analytics and is responsible for developing industry leading anomaly detection models that will identify pending failures of the electric transmission and distribution grid. 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, technologist, 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.

Job Responsibilities

• Supports the research and application of knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions
• Supports the creation of data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets
• Extracts, transforms, and loads data from dissimilar sources from across PG&E for their machine learning feature engineering.
• Supports the application of data science/ machine learning//artificial intelligence methods to develop defensible and reproducible predictive or optimization models,
• Supports the development of mathematical models and AI simulations that represent complex business problems
• Writes and documents python code for data science (feature engineering and machine learning modeling) under senior data scientist guidance.
• Communicates technical information clearly to business.
• Contributes to the development of summary presentations
• Supports peer review exercises
  
  

Qualifications

Minimum:

• Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
• 2 years in data science OR no experience, 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
• Familiarity with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them).
• Knowledge of software engineering, statistics, and machine learning techniques as they apply to data science modeling and deployment.
• Knowledge of commonly used data science and/or operations research programming languages, packages, and tools
• Hands-on experience of data science/machine learning models and algorithms
• Ability to clearly communicate complex technical details and insights to colleagues and stakeholders.
• Knowledge of the mathematical and statistical fields that underpin data science
• Knowledgeable of best practices in software engineering, statistics, and machine learning techniques for data science.
• Knowledge of systems thinking and structuring complex problems
• Ability to collaborate and/or work on a team