Senior Data Scientist

San Ramon, CA, US, 94583

Pacific Gas and Electric Company

Pacific Gas and Electric Company (PG&E) provides natural gas and electric service to residential and business customers in northern and central California.

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Requisition ID # 158655 

Job Category: Accounting / Finance 

Job Level: Individual Contributor

Business Unit: Gas Engineering

Work Type: Hybrid

Job Location: San Ramon

 

 

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.

Gas Transmission Operations 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 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.

 

The Integrity Management organization's vision is to:

 

  • Improve pipeline safety and system reliability with a goal of zero safety incidents.
  • Promote a safety culture throughout all levels of the organization with an emphasis on improving learning from the past and anticipating the future.
  • Apply integrity management principles on a system-wide basis while engaging our stakeholders, from local communities we operate in to our regulators, so they can understand and participate in reducing our risk.
  • Support the design, construction, operation and maintenance of the transmission and distribution pipeline systems through the proactive use of asset knowledge, threat identification, knowledge of threat interaction, data integration and analytical tools to increase operational efficiency, improve system integrity and minimize safety risk to employees and the communities we operate in.

 

Position Summary

 

This Senior Data Scientist position will work on a cross-functional team of Risk Engineers, Risk Analysts, GIS Specialists, and Program Managers to provide business intelligence support involving the use of probabilistic risk modeling methodology for the implementation of risk management duties for PG&E’s gas transmission system. This position will also work collaboratively with data collection organizations to provide data quality assessment and feedback, assess fitness of data for risk modeling, research and adopt industry best practices, develop improvement strategies, and present results to senior leadership and regulatory agencies. This position will report to a Supervising Engineer of Risk Management within the Gas Transmission Integrity Management organization. The Senior Data Scientist is a key position within the Transmission Integrity Management Program (TIMP) team to help ensure PG&E maintains safe and reliable pipelines which comply with federal regulations.

 

Position duties may include (but are not limited to)-

 

 

  • Apply data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models.
  • Writes and documents python code for data science (feature engineering and machine learning modeling) independently.
  • Extracts, transforms, and loads data from dissimilar sources from across PG&E for their machine learning feature engineering.
  • Serves as the technical lead for the development of simple models.
  • Acts as peer reviewer of simple models.
  • Develops and presents summary presentations to management.
  • Keeping up to date with industry innovations, benchmark with industry peers
  • Collaborate with cross-functional teams to develop enterprise level vision for risk assessment.

 

 

 

 

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 (San Ramon, CA).

 

Expected travel- attend monthly in-person team meetings; minor travel to the field (less than once per month).

 

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:$122,000

Bay Area Maximum:$194,000

 

 

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

 

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.
  • 4 years in data science (or 2 years, if possess Master’s Degree).

 

Desired Qualifications:

  • Master’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
  • Competency in software engineering, statistics, and machine learning techniques as they apply to data science deployment.
  • Knowledge of relevant programming languages and database tools - for example SQL, Python, R, MS Access, Excel Macros, ArcGIS
  • Knowledge of statistical theories, concepts, methods, best practices, Monte Carlo simulation and sensitivity analysis.
  • Experience with common data science toolkits, such as R, NumPy, Analytica, RapidMiner, SAS, Anaconda, MS Azure, Amazon, MatLab, Tableau, etc. Excellence in at least one of these is highly desirable
  • Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
  • Understanding of Department of Transportation (DOT) 49 CFR Part 192 codes and regulations, California Public Utility Commission (CPUC) GO 112E
  • Excellent written and verbal communication skills, competency in communication that adapts to the unique needs of different audiences

 

Responsibilities

•     Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform 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,

•     Co-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

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Category: Data Science Jobs

Tags: Anaconda Architecture Azure Business Intelligence Computer Science Consulting Data analysis Data Mining Data quality Econometrics Economics Engineering Excel Feature engineering Finance Machine Learning Mathematics Matlab Monte Carlo NumPy Physics Pipelines Python R RapidMiner Research SAS SQL Statistics Tableau Unstructured data

Perks/benefits: Career development Equity / stock options

Region: North America
Country: United States

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