Expert Data Scientist - PG&E Energy Centers : Job Details

Requisition ID # 164869Job Category: Accounting / FinanceJob Level: Individual ContributorBusiness Unit: Electric EngineeringWork Type: HybridJob Location: OaklandDepartment OverviewElectric Asset Management is responsible for the electric system engineering and planning, asset strategy, and risk management across transmission, distribution, and substation asset families. This centralized, risk-informed approach allows PG&E to manage electric risk, asset and system health, interconnections, and performance by using consistent standards, work methods, prioritization, and program sponsorship, while leveraging lessons learned from inspections and asset data to inform asset management decisions. The organization is accountable for asset planning and strategy, standards and work methods, and asset data management for Electric. The Asset Knowledge Management (AKM) team, within Electric Asset Management, is responsible for the management, quality, and access of PG&E's electric asset data. The team's objective is to maximize the use and ensure the trustworthiness of PG&E's critical electric data assets.Position SummaryThe Data Management & Analytics (DM&A) Product Development team develops client centered delivery of Electric data products that reduce risk and improve operations. The team is looking for an expert level data scientist who thrives on driving engineering and asset management improvements and insights through strategic data science and analysis. The individual in this role must have demonstrated success with cross-functional projects, ability to communicate complex concepts to leadership across the organization, experience driving solutions, detail-oriented, and able to think strategically.In this role, you will work closely with fellow product developers, product managers, and partners throughout the Electric organization to understand their needs to develop valuable products (full-stack development). You will be a thought leader, a tech lead, and be instrumental in building processes, tools, and libraries to improve the efficiency of the team.Designs, develops models, algorithms, and processes using structured and unstructured data from disparate sources and sizes, generating actionable insights using data science and analytics. Works on process improvement and product development/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 product managers, team members, clients, and senior leadership throughout the development cycle, practicing continuous improvement.This position is hybrid, working from your remote office and your assigned work location based on business need.A Reasonable Salary Range IsBay Area Minimum: $140,000Bay Area Maximum: $238,000Job Responsibilities

• Execute full stack analytic product development, through ideation, pipeline, modelling and user interfaces and documentation.
• Work closely with domain experts. Develop relevant domain knowledge in the electric utility.
• Understand and apply machine learning and other analytical modeling methods to develop robust and reliable analytical models, including visualizations, within PG&E's software development environment.
• Mentor junior data scientists and data analysts and drive standardization in process and toolsets across the data science community at PG&E.
• Collaborate with fellow developers within the team for development of scalable data science capabilities.
• Defines, sources, implements, and documents robust, repeatable datasets for internal and cross-organizational use.
• Acts as peer reviewer of complex models.
• Presents findings and makes recommendations to high level leaders.
• Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions which create value.
• Compose and document reusable python functions and modular python code for data science.
• Wrangles and prepares data as input of machine learning model development and feature engineering.
• Applies data science/machine learning/artificial intelligence methods to develop defensible and reproducible predictive or optimization models which involve multiple facets and iterations in algorithm development.
• Extracts, transforms, and loads data from dissimilar sources from across PG&E for their machine learning feature engineering.
• Creates advanced data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets.

• 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).

• Proficiency with the steps in the data science lifecycle: data gathering and preparation, feature engineering, model development and model testing.
• Proficiency with at least one commonly used data science programming language, such as Python, R, Matlab, Scala, or similar.
• Expertise in data science/machine learning models and algorithms, such as Bayesian/statistical inference, NLP, deep learning, classification, clustering, forecasting, time series analysis, or other relevant techniques.
• Experience in utility and energy industries.
• Proficient in Palantir Foundry.
• Proficient in image and natural language processing.
• Experience with systems thinking and structuring complex problems.
• Experience teaching and/or mentoring junior colleagues.
• Experience with programming best practices, including documentation, version control (e.g., Git or equivalent), unit testing, etc.
• Knowledge of the mathematical and statistical fields that underpin data science, such as probability, statistics, optimization, linear algebra, etc.