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Senior Data Scientist- Flexible Location

LocationOakland, California;

Requisition ID # 142842 

Job Category: Accounting / Finance 

Job Level: Individual Contributor

Business Unit: Gas Engineering

Work Type: Hybrid

Job Location: Oakland; Alameda; Alta; Angels Camp; Antioch; Auberry; Auburn; Avenal; Avila Beach; Bakersfield; Balch Camp; Bear Valley; Belden; Bellota; Belmont; Benicia; Berkeley; Brentwood; Brisbane; Buellton; Burney; Buttonwillow; Calistoga; Campbell; Canyon Dam; Canyondam; Capitola; Caruthers; Chico; Clearlake; Clovis; Coalinga; Colusa; Concord; Concord; Corcoran; Cottonwood; Cupertino; Daly City; Danville; Davis; Dinuba; Downieville; Dublin; Emeryville; Eureka; Fairfield; Folsom; Fort Bragg; Fortuna; Fremont; French Camp; Fresno; Fresno; Fulton; Garberville; Geyserville; Gilroy; Grass Valley; Guerneville; Half Moon Bay; Hayward; Hinkley; Hollister; Holt; Huron; Jackson; Kerman; King City; Lakeport; Lemoore; Lincoln; Linden; Livermore; Lodi; Loomis; Los Banos; Lower Lake; Madera; Magalia; Manteca; Manton; Mariposa; Martell; Marysville; Maxwell; Menlo Park; Merced; Meridian; Millbrae; Milpitas; Modesto; Monterey; Montgomery Creek; Morgan Hill; Morro Bay; Moss Landing; Mountain View; Napa; Needles; Newark; Newman; Novato; Oakdale; Oakhurst; Oakley; Olema; Orinda; Orland; Oroville; Palo Alto; Palo Cedro; Paradise; Parkwood; Paso Robles; Petaluma; Pioneer; Pismo Beach; Pittsburg; Placerville; Pleasant Hill; Point Arena; Potter Valley; Quincy; Rancho Cordova; Red Bluff; Redding; Richmond; Ridgecrest; Rio Vista; Rocklin; Roseville; Round Mountain; Sacramento; Salinas; San Bruno; San Carlos; San Francisco; San Francisco; San Jose; San Luis Obispo; San Mateo; San Rafael; San Ramon; San Ramon; Sanger; Santa Cruz; Santa Maria; Santa Nella; Santa Rosa; Selma; Shaver Lake; Sonoma; Sonora; South San Francisco; Springville; Stockton; Storrie; Taft; Tracy; Turlock; Twain; Ukiah; Vacaville; Vallejo; Walnut Creek; Wasco; Washington; Watsonville; West Sacramento; Wheatland; Whitmore; Willits; Willow Creek; Willows; Windsor; Winters; Woodland; Yuba City

Department Overview

Gas Operations is focused on ensuring the safe and reliable flow of natural gas to our customers. As a whole, Gas Operations is responsible for all aspects of PG&E's gas distribution and transmission operations, including planning, engineering, maintenance and construction, restoration and emergency response.This position is located within the Transmission Integrity Management department within PG&E's Asset Management and Systems Operation (AM&SO) Organization. Gas Operations AM&SO is responsible for maintaining over 6,000 miles of gas transmission pipelines throughout California. This Department is responsible for the overall administration and implementation of the Transmission Integrity Management Program (TIMP) and the evaluation of overall risk to the gas transmission system. This includes overseeing the completion of integrity management assessments, identifying High Consequence Areas (HCA), maintaining PG&E's assessment plan as required by 49 CFR Subpart O, and managing PG&E's overall gas risk management program.

Position Summary

Designs, develops, and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating actionable insights for strategy and policy development, process improvement, and product enhancement. Works on technical development phases: data engineering, analytics/modeling, and visualization/user interface. Interacts with technical and non-technical clients to resolve analysis and technical issues. Works with teams, clients, and senior leadership throughout the development cycle practicing continuous improvement.

Data scientist will review current threat algorithm to determine correlations between data.  Tasks may include validation of current risk model, comparison of events to current risk score, implement several different machined learned models to determine performance/optimization.  Individual must be comfortable working with a wide range of stakeholders and be able to work independently to discover hidden solutions within the data.  Must be able to utilize large data sets for a variety of data mining/data analysis methods.

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.

Incumbent should expect to travel to San Ramon, CA for projects, meetings, trainings, etc.

Location is flexible within the PG&E Service Territory, please note hiring leader will make final decision of what are appropriate headquarters for the role based on business need.

Position could require a minimal amount of travel.

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: $118,000
Bay Area Maximum:$188,000
California Minimum:$112,000
California Maximum: $179,000

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


Minimum Qualifications: 

• Bachelor’s Degree in Computer Science, Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience

• Job-related experience (e.g. data analytics and modeling), 5 years, OR Master’s Degree and job-related experience, 3 years, OR Doctorate

Desired Qualifications:

•           Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience, 1 year

  • Knowledge, Skills, Abilities and (Technical) Competencies
  • Experience with the elements of the data management lifecycle (data acquisition, security, storage, architecture, integration, governance, compliance, reference data management, data quality and metadata) and best practices
  • Knowledge of relevant project management tools, theories and techniques as needed to support the timely and successful execution of project requirements
  • Knowledge of commonly used data science and/or operations research programming languages, packages, and tools
  • Understanding of data science/machine learning models and algorithms 
  • Ability to synthesize complex information into clear insights and translate those insights into decisions and actions
  • Ability to clearly communicate complex technical details and insights to colleagues and stakeholders
  • Knowledge of the mathematical and statistical fields that underpin data science
  • Ability to collaborate and/or work on a team
  • Knowledge of systems thinking and structuring complex problems


•           Shares and collaborates with other PG&E data science professionals.

•           Works closely with domain experts to develop relevant domain knowledge in the electric and gas utility, as well as knowledge of related datasets.

•           Gathers, cleans, transforms, and/or reduces data from dissimilar sources from across PG&E.

•           Works with business partners to advance business processes, based on analytical findings.

•           Applies machine learning and other analytical modeling methods to develop robust and reliable analytical models, including visualizations, within PG&E’s software development environment.

•           Documents data sources, methodology, and model evaluation metrics.

•           Serves as the technical lead for the development of simple models.

•           Develops and presents summary presentations to management.

•           Position will work with engineers on calibration of risk model through field findings.

•           Utilization of field findings can be used to develop machine learned models to better fit data.

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  • Accounting / Finance, Oakland, California, United StatesRemove