Principal Data Scientist

3 weeks ago

Oakland, United States PG&E Corporation Full time

Requisition ID # 157227

**Job Category**: Accounting / Finance
**Job Level**: Manager/Principal
**Business Unit**: Gen Counsel, Ethics, Risk & Compliance
**Work Type**: Hybrid
**Job Location**: Oakland

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 Principal Data Scientist will support the enterprise risk analytics function of providing quantitative risk analysis and modeling for effectively managing a variety of enterprise and operational risks that PG&E face. The work that the position performs will inform important decisions at PG&E and support various regulatory filings such as Risk Assessment and Mitigation Phase (RAMP), General Rate Case (GRC), Wildfire Mitigation Plan (WMP). You will work on continuous improvement of quantitative assessment of risk and its mitigations, and evolvement of the analytical tools (data processing, algorithms, python codes, excel files, foundry, etc) that enable consistent and useful evaluation of the risks and mitigations across the company. 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. You will also review and validate existing methods, assumption, algorithms and models used and work on improving and advancing risk analytics at PG&E.

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

**A reasonable salary range is**:
**Bay Area Minimum**: $159,000
**Bay Area Maximum**: $271,000

Job Responsibilities

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.
Document data sources, methodology, and model evaluation metrics.
Mentor junior data scientists, analysis and modeling risk analysts, risk analysts and drive standardization in process and toolsets across the data science community at PG&E
Collaborate with analytics platform owners to prioritize and drive development of scalable data science and risk and mitigation modeling capabilities at PG&E
Manage the development of complex quantitative models and tools
Validate risk models, inputs, outputs, algorithms, and codes
Assess existing methods used in risk and mitigation modeling at PG&E and advocate, drive, and implement evolution and improvements
Recognize and prioritize the most important work related to risk analytics to achieve highest operational impact and drive risk-informed decision making
Utilize deep understanding of business and risk drivers and financial levers to provide strategic decision support
Assess business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
Present findings and make recommendations to executive leadership and cross-functional senior management
Discuss and explain the risk analysis and modeling methodology to internal and external stakeholders including presenting to public workshops
Research the quantitative methods and findings related to risk and mitigation analysis relevant for PG&E

**Qualifications**:
**Minimum**:
Doctoral degree in computer science, econometrics, economics, engineering, mathematics, applied sciences, statistics, machine learning or job-related discipline
4 years of job-related experience

**Desired**:
Relevant industry experience (electric or gas utility, analytical consulting, etc), 8 years
Experience in quantitative risk analysis or Probabilistic Risk Assessment
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
Ability to work independently and proactively and to tak

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