Data Scientist

Requisition ID # 174643 

Job Category: Accounting / Finance 

Job Level: Individual Contributor

Business Unit: Customer & Corporate Affairs

Work Type: Hybrid

Job Location: Oakland

Department Overview

The Rates department within PG&E’s Customer & Corporate Affairs organization develops and provides expertise on gas and electric customer rates in regulatory proceedings at the California Public Utilities Commission (CPUC) and the Federal Energy Regulatory Commission (FERC). 

With a primary focus on ensuring fair, equitable, and stable rates for our customers, the Rates department designs rate plans, conducts cost of service analyses, forecasts revenues, and analyzes trends and drivers impacting customer rates and bills.  We support other organizations in understanding energy usage to enhance various programs and policies that support our customers.

Position Summary

PG&E is seeking a Data Scientist to support cost analyses used in PG&E’s electric and gas rate design proposals in regulatory proceedings.  Data Science is foundational for ensuring that our customers’ rates are designed fairly and equitably.  Senior Data Scientist in Cost-of-Service team works cross-functionally to design, develop, and execute scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating defensible, valid, scalable, reproducible and documented machine learning and artificial intelligence models (predictive or optimization) for problem solving and strategy development. Additionally, the Senior data scientist educates the non-technical community on advantages, risks, and maturity levels of data science solutions and participates in internal and external communities of practice in data science/artificial intelligence/machine learning to advance knowledge in the field.

Data Scientist supports evidentiary hearings including assisting expert witnesses on developing or revising proposals, summarizing and evaluating others’ proposals, and responding to external requests.  Utility business knowledge, an understanding of economic and financial concepts, and quantitative modeling such as programming, statistics and mathematics are key skills to be successful in this role. 

The successful candidate will embody a balance of data science expertise, intellectual curiosity, structured thinking, written and verbal communication skills, and team-orientation.

This position is hybrid, working from your remote office and Oakland General Office once per week and based on business needs. 

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. 

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

A reasonable salary range is:

Bay Area Minimum:    $ 102,000

Bay Area Maximum:    $ 162,000

Job Responsibilities

• Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform revenue allocation and rate design related generation, transmission and distribution cost-of-service business decisions.
• Creates 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.
• Develops mathematical models and AI simulations that represent complex business problems.
• Writes and documents python code for data science (feature engineering and machine learning modeling) independently.
• Serves as the technical lead for the development of simple models.
• Develops and presents summary presentations to business.
• Act as peer reviewer of simple models
• Adopts efficient tools and processes and ensures robust quality control of results.
• Prepares and maintains documentation of models and procedures.
• Presents key insights to influence decision making.
• Collaborates with teams across PG&E.
• Responds to time-sensitive requests related to the subject matter including modeling, analytics and visualization.

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

• Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience

• Knowledge of finance and economics used in utility rate design

• Demonstrated knowledge of and abilities with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them

• Competency in software engineering, statistics, and machine learning techniques as they apply to data science deployment

• Competency in commonly used data science and/or operations research programming languages, packages, and tools.

• Hands-on and theoretical experience of data science/machine learning models and algorithms

• Ability to synthesize complex information into clear insights and translate those insights into decisions and actions. Demonstrated ability to explain in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.

• Competency in the mathematical and statistical fields that underpin data science

• Mastery in systems thinking and structuring complex problems

• Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies