Data Scientist, Expert

Requisition ID # 174571 

Job Category: Accounting / Finance 

Job Level: Individual Contributor

Business Unit: Strategy & Growth

Work Type: Hybrid

Job Location: Oakland

Department Overview

Over 6,500 coworkers in Electric T&D ensure the delivery of clean, safe, reliable and affordable energy to nearly 16 million people in Northern and Central California. The Electric T&D Team is responsible for ensuring the electric grid's reliability and resiliency through the ongoing maintenance and operations of PG&E's 100,000 miles of distribution lines and over 18,000 miles of Transmission lines. Coworkers in Electric T&D's actively engage in the Lean Methodology through the use of Visual Management in Operating Reviews to cross-functionally identify and solve problems,  and create standard work. By working together as One Electric. One Team. We are delivering for our hometowns.   

This position is headquartered in Oakland, CA. This position is “hybrid”, with the expectation of being in the office 1x/week (subject to change due to business needs. This position is within the Transmission Tools and Modeling (TTM) team. TTM develops the analytical tools, data solutions, and power system models that enable informed transmission planning and operational decision-making. The team combines expertise in power system analysis, software development, data engineering, and process automation to build and maintain study cases, planning models, databases, and forecasting methodologies used across the organization. Working closely with planners, engineers, operations, and business partners, the team delivers innovative solutions that improve study efficiency, data quality, and modeling accuracy while supporting the reliable and cost-effective planning of the electric grid. The group is focused on modernizing workflows, leveraging advanced analytics, and creating scalable tools that help transform complex grid data into actionable insights.

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.​

A reasonable salary range is:​

Bay Area Minimum: $​140,000

Bay Area Maximum: $​238,000

&/OR​

California Minimum: $​133,000

California Maximum: $226,000

Position Summary

Designs, develops, and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating for  defensible, valid, scalable, reproducible and documented machine learning and artificial intelligence models (predictive or optimization) for problem solving and strategy development. Participates in internal and external communities of practice in data science/artificial intelligence/machine learning to advance knowledge in the field. Educates the non-technical community on advantages, risks, and maturity levels of data science solutions.

Responsibilities:

• Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
• Creates advanced 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
• Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm development.
• Wrangles and prepares data as input of machine learning model development and feature engineering
• Writes and documents reusable python functions and modular python code for data science.
• Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
• Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions that create value.
• Presents findings and makes recommendations to senior management.
• Act as peer reviewer of complex models

Qualifications

Minimum Qualifications:

• Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
• 6 years in data science (or no experience, if possess Doctoral Degree or higher, as described above).

Desired Qualifications:

• Doctoral Degree or higher 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
• Active participation in the external data science/artificial intelligence/machine learning community of practice, as demonstrated through volunteering in professional organizations for the advancement of the field, presentations in conferences or publications to disseminate data science knowledge and topics, or similar activities.
• Competency with data science standards and processes (model evaluation, optimization, feature engineering, etc) along with best practices to implement them
• 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
• Competency with commonly used data science and/or operations research programming languages, packages, and tools for building data science/machine learning models and algorithms  
• Proficiency in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
• Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders
• Mastery of the mathematical and statistical fields that underpin data science
• Ability to develop, coach, teach and/or mentor others to meet both their career goals and the organization goals
• Previous experience working with utility data
• Previous experience with load forecasting, working with utility customer data, consumption patterns, and outage data
• Working knowledge power flow concepts and tools such as PLSF, PSS®E, TARA, PROMOD, PLEXOS
• Previous experience with cloud-based infrastructure services across compute, storage, network, and operating system layers along with an understanding of cloud architecture