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Senior Data Scientist - Flexible Location, CA

LocationSan Francisco, California;

Requisition ID # 114470 

Job Category : Accounting / Finance 

Job Level : Individual Contributor

Business Unit: Finance

Job Location : San Francisco

Department Overview
The Enterprise Risk and Operational Risk Management (EORM) organization is responsible for enabling the business to effectively manage risk in key areas of the enterprise. EORM organization is charged with overseeing all operational risk management related to PG&E’s operations and public safety including evaluating risks associated with wildfires, nuclear, dams, natural gas, cyberattacks and natural disasters.

Position Summary
The headquarter location will be determined by hiring leader and successful candidate.  You must be able to work out of the Oakland office at least once a week.

You will be responsible for designing, developing, and executing 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. You will also work on technical development phases: data engineering, analytics/modeling, and visualization/user interface; interact with technical and non-technical clients to resolve analysis and technical issues; and work with teams, clients, and senior leadership throughout the development cycle practicing continuous improvement.

Responsibilities:

  • Share and collaborate with other PG&E data science professionals.
  • Work closely with domain experts to develop relevant domain knowledge in the electric and gas utility, as well as knowledge of related datasets.
  • Gather, clean, transform, and/or reduce data from dissimilar sources from across PG&E.
  • Work with business partners to advance business processes, based on analytical findings.
  • Apply machine learning and other analytical modeling methods to develop robust and reliable analytical models, including visualizations, within PG&E’s software development environment.
  • Document data sources, methodology, and model evaluation metrics.
  • Serve as the technical lead for the development of simple models.
  • Develop and present summary presentations to management

Qualifications

Minimum:

  • Bachelor’s degree in computer science, econometrics, economics, engineering, mathematics, applied sciences, statistics or job-related discipline or equivalent experience
  • 5 years of data analytics and modeling experience; OR 3 years of data analytics and modeling experience and a Master’s degree in a related field; OR a doctorate in a related field

Desired:

  • Master’s or PhD degree in statistics, data science, decision science, computer science, quantitative analysis, information systems, operations research, business, engineering, financial engineering, economics, or other equivalent fields
  • Strong foundation of probability, probability distributions, statistics and risk analysis
  • Competent programming skills in a language especially in Python and familiarity with Git
  • Demonstrated experience of Monte Carlo simulation methods and models
  • Familiarity and experience with Bayesian statistics and inference
  • Experience in quantitative risk analysis or Probabilistic Risk Assessment
  • Ability to work independently and proactively and to take initiative to improve analytical methods or processes
  • Experience with the elements of Model Lifecycle Management
  • Experience using retrieving data from structured database using SQL
  • Strong Excel and PowerPoint skills
  • Strong data visualization skills and techniques for communicating risk-related data and modeling results in a clear and visually compelling manner
  • Strong problem-solving, analytical, and organizational skills with attention to detail
  • Ability to share knowledge, information and progress with the team effectively and efficiently
  • Effectively copes with change, makes decisions and acts without having complete information and comfortably handles risk and uncertainty.
  • Ability to research and apply knowledge, skills, and techniques to risk analysis
  • Ability to manage conflicts in a positive, non-abrasive manner
  • Ability to communicate with peers, leadership, and stakeholders in a clear and effective manner
  • Highly motivated and self-driven
  • Ability to collaborate with people with diverse background and skillsets
  • ability to effectively manage and prioritize multiple and diverse tasks and adhere to tight deadlines
  • Knowledge of the business and its environment, key issues, and trends
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