Principal Data Scientist, Data Analytics Team, Grid Integration and Innovation

Job Posting Date: August 12, 2017
Requisition #: 54202065-E01
Job Category: Business Operations / Strategy
Job Level: Manager/Principal
Employment Type: Management
Business Unit: Strategy and Policy
Schedule: Full-time
City: San Francisco
Company

Based in San Francisco, Pacific Gas and Electric Company, a subsidiary of PG&E Corporation (NYSE:PCG), is one of the largest combined natural gas and electric utilities in the United States. And wedeliver some of the nation’s cleanest energy to our customers in Northern and Central California. For PG&E, ‘Together, Building a Better California’ is not just a slogan. It’s the very core of our mission and the scale by which we measure our success. We knowthat the nearly 16 million people who do business with our company count on our more than 24,000 employees for far more than the delivery of utility services. They, along with every citizen of the state we call home, also expect PG&E to help improve theirquality of life, the economic vitality of their communities, and the prospect for a better future fueled by clean, safe, reliable and affordable energy.

Pacific Gas and Electric Company is an Affirmative Action and Equal Employment Opportunity employerthat actively pursues and hires a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, sex, age, religion, physical or mental disability status, medical condition, protectedveteran status, marital status, pregnancy, sexual orientation, gender, gender identity, gender expression, genetic information or any other factor that is not related to the job.

Department Overview

The Grid Integration and Innovation (GII)organization is responsible for designing, testing, and integrating innovative solutions with the purpose of accelerating PG&E’s transition to the sustainable grid of the future. This includes technology pilots, such as: developing the first Distributed EnergyResources Management Systems (DERMS) that enables the remote dispatchability of energy storage, or PG&E’s partnership with BMW to test electric vehicles that allow for the bi-directional flow of energy, both to the car for charging and from the car back to thegrid in times of load need. In addition to technology pilots, GII is also responsible for shaping the regulatory framework that will transition PG&E towards a future with distributed energy resources (solar, wind, storage, demand response, etc.) deeplyintegrated into the electricity grid. This includes pairing greenhouse gas emissions policies with changes to the utility’s capital focused decoupled business model, allowing revenue recovery alternatives that are focused on reliability and customer choice.

In order to meet these goals, GII’s Data Analytics team aims to utilize best in class modeling techniques and industry leading data science to drive PG&E’s transition to the sustainable grid of the future through quantitative decision-making. This workmoves beyond descriptive reporting and is focused on driving the business forward through applied statistics, predictive and prescriptive analytics, and machine learning. The underlying foundation is the largest smart meter usage databases in the US, that whencombined with distribution grid data, equipment ratings, program engagement, customer demographics, and other data sources has unprecedented potential.

Past projects include:
*Development of algorithms focused on outlier identification, eventprediction, and trend identification.
*Assessing the impact and viability of grid edge technology implementations and distributed energy resources
*Forecasting market potential and adoption for demand side management technologies, programs, and services
*Optimizing non-wires alternative resource portfolio, location, and performance
*Analyzing customer demographic, program participation and SmartMeter interval data to build program targeting propensity models

Position Summary

We arelooking for a full-time team member to work on one or more of the areas mentioned above. In this role you will work collaboratively with partners from across the entire utility, including IT, to provide targeted actionable insights and best in class analyticsdeployments. This role will also hold shared responsibility with division leadership on coaching, mentoring, and teaching other members of the PG&E analytics community with the goal of improving the utility’s capabilities, processes, general analytics maturity.It is the perfect role for someone who is looking to compound their positive impact through unlocking the capabilities of others via coaching and collaborative project execution.

Qualifications

Minimum Qualifications:
*Bachelor’s degree inoperations research, statistics, economics, engineering, computer science, or similar quantitatively focused subject areas
*Job-related experience, 10 years, OR Masters Degree and job-related experience, 8 years, OR Doctorate Degree and job-related experience,5 years
*Experience in data modeling, 6yrs
*Mastery of relevant analytics and distributed computing languages – for example SQL, python, pySpark, SCALA
*Proficiency with data science techniques including logistic regression, clustering, randomforests, neural networks, Bayesian networks, etc.
*Experience with data visualization tools such as Tableau, R Shiny, D3.js, etc.

Desired Qualifications:
*Dedication to the continuous improvement of one’s self and team
*Proven commitmentto best in class documentation
*Knowledge of program management theories, concepts, methods, best practices, and techniques as needed to perform at the job level
*Knowledge of data model design philosophies and methodologies for data warehouse and OLTPsystems
*Excellent oral and written communication skills
*Experience in the energy/clean tech industry

Responsibilities

Scoping and Project Planning
*Determine the best analytical approach to solving a business need while balancingtime requirements, business process requirements, statistical rigor, data quality, and other considerations.
*Work collaboratively a diverse team to assign and perform tasks aimed at reaching a shared gal.

Data Science & Analytics
*Abilityto use and synthesize data from various sources into a user-friendly model and actionable insights
*Utilization of grid operations, customer demographic, and similar data to inform decisions
*Leads development of statistical methods, analytical modeling,and machine learning techniques such as segmentation, clustering, time series analysis, optimization, forecasting, sensitivity studies, dimensionality reduction, gradient boosting, both supervised and unsupervised learning, etc.
*Excellent written documentationincluding: assumptions, methodology determination, in line, and end of project
*Coaching and developing the data science skills of others

Summary Presentation and Visualization
*Create or support development of summary presentations forsenior management
*Create or support development of streamlined visuals for end-users

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