Principal Data Scientist
Requisition ID # 145149
Job Category: Accounting / Finance
Job Level: Manager/Principal
Business Unit: Information Technology
Work Type: Hybrid
Job Location: Oakland
The Data Science & Decision Science Department is both a “Delivery” team that is a sophisticated practitioner of data science and a “Center of Excellence” team that supports other practitioners in an enterprise-wide Hub & Spoke analytics adoption model.
As a Delivery team, this Department uses industry leading data science and change management practices to drive PG&E’s transition to the sustainable grid of the future. The Department works cross-functionally across the company to enable data driven decisions applying analytics, as well as improvements to relevant business processes. Deployed to some of PG&E’s highest priority arenas, the Department does not specialize in a traditional utility domain, such as asset management or program administration, but instead specializes in extracting useful insights from disparate data sets and facilitating actions informed by these insights.
As a Center of Excellence team, this Department listens to the needs of practitioners across the company, along with emerging industry practices, and builds standards, processes, tools, knowledge and best practices that meet the current and future needs of the enterprise.
This team works on a wide variety of difficult problems, offering great variety in the work, and constant opportunity to explore and learn. Current and past engagements include:
Creating wildfire risk models that are used by regulators and the utility to prioritize asset management
Developing computer vision models that improve, accelerate, and automate asset inspections processes
Predicting electric distribution equipment failure before it occurs, allowing for proactive maintenance
Forming the analytical framework behind PG&E’s Transmission Public Safety Power Shutoff
Optimizing non-wires alternative resource portfolios, like the Oakland Clean Energy Initiative, including location and resource adequacy considerations
Analyzing customer demographic, program participation, and SmartMeter interval data to build program targeted propensity models, e.g. for customer owned distributed energy resource technologies
Identifying and investigating anomalous customer natural gas usage, in order to resolve dangerous customer side leaks
PG&E is looking for a Technical Leader in Data Science Delivery at the Principal level with large experience in the design and delivery of client-oriented data science products. In this role, the successful candidate will be uniquely positioned at the forefront of utility industry analytics, having the opportunity to advance PG&E’s triple bottom line of People, Planet, and Prosperity. Spearheading technical work as part of a cross functional team (including data engineers, data scientists, technologists, subject matter experts, and change management professionals) this individual will lead the design and delivery of data science products using advance analytics methods such as machine learning and advanced statistics. As part of the Enterprise Decision Science program portfolio, these data science products will focus on improving strategic decision making and operational processes in different PG&E business areas. Due to the operational impact of this type of work, the ability to establish and maintain strong relationships with business partners, design value-adding data science solutions that realize PG&E’s strategic agenda, and strive for continuous improvement and optimization of data science models are key leadership components of this role. The technical leadership in delivery work will also be both hands-on as well as leading work by other data science team members (depending on scope and complexity of work).
The responsibilities of these positions include:
As technical team leader for his/her team, s/he will lead all technical aspects of delivery including identification of value-adding data science use cases; designing data science and advance analytics solutions to meet use case requirements; leading code review sessions; offering feedback in peer review exercises; deploying algorithms in production environments; optimizing for data and model drift; testing and continuous improvement of code; etc.
Lead technical sessions with stakeholders and other key delivery partners such as functional and business areas, IT enablers, data stewards, product owners, etc.
Proactively identify decision science delivery opportunities that tackle institutional priorities. Reach out to business owners and other stakeholders making a case for the impact of data science in decision making quality and the realization of PG&E institutional agenda.
Advise and coach other team members in data science techniques, practices and technologies (i.e. programming and coding for data science) as well as deliver hands-on data science work as part of the delivery, if needed.
Present findings and make recommendations to officers and cross-functional management.
Build and maintain strong relationships with business units and external agencies.
This position reports to the Director, Enterprise Decision Science/Data Science & Analytics Products.
• Works closely with domain experts to develop relevant domain knowledge in the electric and gas utility, as well as knowledge of related datasets.
• Documents data sources, methodology, and model evaluation metrics.
• Collaborates with analytics platform owners to prioritize and drive development of scalable data
• Mentors junior data scientists and drives standardization in process and toolsets across the data science community at PG&E.
• Works with enterprise leaders as an advocate for digital transformation of the business through the adoption of data science, analytics, and data-driven business processes.
• Applies machine learning and other analytical modeling methods to develop robust and reliable analytical models, including visualizations, within PG&E’s software development environment.
• Manages development of complex quantitative models and tools.
• Recognizes and prioritizes the most important work related to data science models to achieve
highest operational impact for analytics in the business.
• Utilizes deep understanding of business drivers and financial levers to provide strategic decision
• Presents findings and makes recommendations to executive leadership and cross-functional management.
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. We would not anticipate that the individual hired into this role would land at or near the top half of the range described below, but the decision will be dependent on the facts and circumstances of each case.
A reasonable salary range is:
Bay Area Minimum: $151,000.00
Bay Area Mid-point: $204,000.00
Bay Area Maximum: $257,000.00
California Minimum: $143,000.00
California Mid-point: $194,000.00
California Maximum: $244,000.00
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.
Bachelor’s Degree in Computer Science, Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience
Job-related experience (e.g. data analytics and modeling), 10 years, OR Master’s Degree and job-related experience, 8 years, OR Doctorate and job-related experience, 5 years
Knowledge, Skills, Abilities and (Technical) Competencies
• Experience/knowledge of Palantir Foundry, AWS Sagemaker, Confluence, JIRA, Python, PySpark, Scikit-learn, SQL
• Proficiency with the elements of the data management lifecycle (data acquisition, security, storage, architecture, integration, governance, compliance, reference data management, data quality and metadata) and best practices
• Competency with relevant project management tools, theories and techniques as needed to support the timely and successful execution of project requirements
• Knowledge of industry trends and current issues in job-related area of responsibility as demonstrated through peer reviewed journal publications, conference presentations, open source contributions or similar activities
• Proficiency with commonly used data science and/or operations research programming languages, packages, and tools
• Expertise in data science/machine learning models and algorithms
• Proficient at systems thinking and structuring complex problems
• Proficiency in synthesizing complex information into clear insights and translating those insights into decisions and actions
• Ability to clearly communicate complex technical details and insights to colleagues, stakeholders, and leadership
• Knowledge of the mathematical and statistical fields that underpin data science
• Ability to develop, coach, teach and mentor others to meet both their career goals and the organization goals