Data Scientist, Expert

Requisition ID# 164849

Job Category: Accounting / Finance

Job Level: Individual Contributor

Business Unit: Operations - Other

Work Type: Hybrid

Job Location: Auburn; Oakland

Department Overview

PG&E's Power Generation organization operates and maintains PG&E's hydroelectric, fossil, solar generation and battery storage facilities, providing approximately 5,500 megawatts of generating capacity for our customers. Our coworkers are dedicated to delivering safe, reliable and cost-effective generation to California in an environmentally responsible manner. Our hydro facilities include 58 conventional hydro powerhouses, a pumped-storage facility, 98 reservoirs, 165 dams and morethan 350 miles of canals, flumes and other water conveyances. Natural gas-fired plants in operation are Humboldt Bay Generating Station in Eureka; Colusa Generating Station in Colusa County and Gateway Generating Station in Antioch. Several utility-scale solar generation plants are operated and maintained, as well as PG&E's successful entry into battery energy storage systems, with our Elkhorn Battery facility at Moss Landing in Monterey County.

Position Summary

This position, in partnership with a peer Analysis & Modeling Risk Analyst, will primarily lead the risk analysis and quantification efforts for all Power Generation risks. The successful candidate will be instrumental in executing the transition to a new risk management framework that is integrated across the organization, and that will provide necessary granularity and integration to align with PG&E's enterprise risk management framework.

This position will work closely with stakeholders internal to Power Generation, including those within Power Generation's Asset Engineering (including Asset Knowledge Management), Risk & Compliance, Business Planning, Asset Strategy, Project Execution, and other teams. This position will also engage with stakeholders external to Power Generation, including those within the Enterprise and Operational Risk Management, Business Plan Deployment, Emergency Preparedness & Response, Geosciences, and other teams.

In this role, you will quickly learn and apply our current risk framework. This includes bowtie development, evaluation of controls and mitigations, and support ad hoc risk analysis in support of our asset strategy partners.Excellent Excel auditing, implementation of Python codes, and Foundry code repository is required.This role will also require detailed understanding of our prioritization models and identifying the gaps with our current bowtie models that will need to be addressed and solved. In the transition to a new risk-informed evaluation approach, the successful candidate will work closely with different stakeholders to incorporate requirements, and plan and execute the new models.

The prospective candidate is organized, technically oriented, can grasp concepts quickly, and adapt to new information.The successful candidate will be instrumental in managing the transition to a new risk-informed evaluation methodology that will provide appropriate level of granularity and align with PG&E's Enterprise & Operational Risk Management framework.

This position is hybrid, working from your remote office and your assigned work location based on business need (Oakland or Auburn). Currently, the team goes into the office approximately once a week or as required based on specific meetings and workshops.

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: $140,000

Bay Area Maximum: $238,000

&/OR

California Minimum: $133,000

California Maximum: $226,000

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

Position Duties (may include but are not limited to)

• Lead development and maintenance of quantitative risk models in support of asset management system, asset investment planning, enterprise and operational risk management objectives, and regulatory proceedings.

• Be able to effectively communicate how the quantitative risk models work and explain the results to risk owners and the leadership team.

• Deliver in-depth data analysis using Python or Foundry platform to provide insights to management and facilitate Power Generation business and risk decisions

• Promote data-driven decision-making, establishing a culture of risk quantification across the Functional Area.

• Develop and coordinate presentation materials for various levels of management, including company Officers and members of the Board of Directors.

• Assist in the development and management of Power Generation's Risk Register and statistical and probabilistic methodologies for risk assessment and prioritization.

Job Responsibilities

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

• Creates advanced 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 that involve multiple facets and iterations in algorithm development.

• Wrangles and prepares data as input of machine learning model development and feature engineering

• Writes and documents reusable python functions and modular python code for data science.

• Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.

• Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions that create value.

• Presents findings and makes recommendations to senior management.

• Acts as peer reviewer of complex models

Qualifications-

Minimum:

• Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.

• 6 years in data science (or no experience, if possess Doctoral Degree or higher, as described above).

Desired:

• 5+ years of experience in power generation business and risk management.

• Doctoral Degree or higher in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.

• Experience in Foundry code repository program using PySpark

• Experience in asset management (Power Generation)

• Experience in General Rate Case (GRC) and Risk Assessment & Mitigation Phase (RAMP) Filings

• Program experience with Python and Github

• Demonstrated experience in visualization tools and techniques and refined visualization skills for communicating risk quantification results and progress.

• Demonstrated analytical and critical thinking skills with the ability to synthesize complex issues into easy-to-understand concepts.

• Good oral and communication skills.

• Experience building relationships across multiple functions and facilitating the decision-making process.

• Technically oriented and ability to manage multiple workstreams concurrently.

• Self-starter, sense of urgency and accountability.

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