Data Scientist, Principal

Requisition ID# 164273

Job Category: Accounting / Finance

Job Level: Manager/Principal

Business Unit: Electric Engineering

Work Type: Hybrid

Job Location: Oakland; Alameda; Alta; American Canyon; Angels Camp; Antioch; Auberry; Auburn; Avenal; Avila Beach; Bakersfield; Balch Camp; Bay Point; Bear Valley; Belden; Bellota; Belmont; Benicia; Berkeley; Brentwood; Brisbane; Buellton; Burney; Buttonwillow; Calistoga; Campbell; Canyon Dam; Canyondam; Capitola; Caruthers; Chico; Clearlake; Clovis; Coalinga; Colusa; Concord; Concord; Corcoran; Cottonwood; Cupertino; Daly City; Danville; Davis; Dinuba; Downieville; Dublin; Emeryville; Eureka; Fairfield; Folsom; Fort Bragg; Fortuna; Fremont; French Camp; Fresno; Fresno; Fulton; Garberville; Geyserville; Gilroy; Goodyear; Grass Valley; Guerneville; Half Moon Bay; Hayward; Hinkley; Hollister; Holt; Houston; Huron; Jackson; Kerman; King City; Lakeport; Lemoore; Lincoln; Linden; Livermore; Lodi; Loomis; Los Banos; Lower Lake; Madera; Magalia; Manteca; Manton; Mariposa; Martell; Marysville; Maxwell; Menlo Park; Merced; Meridian; Millbrae; Milpitas; Modesto; Monterey; Montgomery Creek; Morgan Hill; Morro Bay; Moss Landing; Mountain View; Napa; Needles; Newark; Newman; Novato; Oakdale; Oakhurst; Oakley; Olema; Orinda; Orland; Oroville; Palo Alto; Palo Cedro; Paradise; Parkwood; Paso Robles; Petaluma; Pioneer; Pismo Beach; Pittsburg; Placerville; Pleasant Hill; Point Arena; Potter Valley; Quincy; Rancho Cordova; Red Bluff; Redding; Richmond; Ridgecrest; Rio Vista; Rocklin; Roseville; Round Mountain; Sacramento; Salida; Salinas; San Bruno; San Carlos; San Francisco; San Francisco; San Jose; San Luis Obispo; San Mateo; San Rafael; San Ramon; San Ramon; Sanger; Santa Cruz; Santa Maria; Santa Nella; Santa Rosa; Selma; Shaver Lake; Sonoma; Sonora; South San Francisco; Springville; Stockton; Storrie; Taft; Tracy; Turlock; Twain; Ukiah; Vacaville; Vallejo; Walnut Creek; Wasco; Washington; Washington D.C.; Watsonville; West Sacramento; Wheatland; Whitmore; Willits; Willow Creek; Willows; Windsor; Winters; Woodland; Yuba City

Department Overview

The System Performance, Reliability and Resiliency Strategy team within the overall Electric Transmission and Distribution Engineering organization is responsible for planning, organizing, and managing the resources necessary to successfully execute PG&E's Electric Reliability Strategy and initiatives. This team of forward-thinking individuals will be tasked with deploying technology and infrastructure and influencing the organization to achieve the company's reliability goals. The team is responsible for implementing programs required to modernize the electric grid allowing for safe, resilient and efficient operations. The team participates in a cross functional team of internal and consulting participants being tasked with leading the transition of a project from development and testing to being operational for each phase of each project.

Position Summary

Within the System Performance, Reliability and Resiliency Strategy team, this position reports to the Sr Manage, Predictive Analytics and is responsible for developing industry leading anomaly detection models that will identify pending failures of the electric transmission and distribution grid. In this role the successful candidate will be uniquely positioned at the forefront of utility industry analytics. Working as part of cross functional teams, including data engineers, data scientists, technologist, and subject matter experts - this individual will lead the development of data science capabilities that could lead to paradigm changes in how the utility operates.

• 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.

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.

Bay Minimum: $159,000
Bay Maximum: $271,000

&/OR

CA Minimum: $204,000
CA Maximum: $257,000

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

Job Responsibilities

• Creates, applies, and evaluates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets
• Applies and evaluates 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.
• Writes and documents complex and reusable python functions as well as multi-modular python code for data science.
• As a technical leader, provides thought leadership in the use of a ML algorithms for solving business problems.
• Mentors junior data scientists and drives standardization in process and toolsets across the data science community at PG&E.
• Collaborates with analytics platform owners to prioritize and drive development of scalable data science capabilities.
• Acts as peer reviewer for complex models/AI algorithm proposals.
• Recognizes and prioritizes the most important work related to data science models to achieve highest operational and strategic impact for analytics in the business.
• 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.
• Presents findings and makes recommendations to executive leadership and cross-functional management

Qualifications

Minimum:

• Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics, or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
• 8 years in data science or 2 years, if possess Doctoral Degree or higher, as described above

Desired:

• Doctoral Degree or higher in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
• Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience.
• Experience with time series data sets and anomaly detection algorithms
• Thought leadership in the external data science/artificial intelligence/machine learning community of practice, as demonstrated through peer reviewed journal publications, intellectual property/patent achievements, conference presentations, volunteering in professional organizations for the advancement of the field, participation in externally sponsored research projects, open-source contributions, or similar activities.
• Proficiency with data science standards and processes (model evaluation, optimization, feature engineering, etc) along with best practices to implement them.
• Proficiency with commonly used data science and/or operations research programming languages, packages, and software tools for building data science/machine learning models and algorithms
• Mastery in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
• Ability to clearly communicate complex technical details and insights to colleagues, stakeholders, and leadership
• Leadership in developing, coaching, teaching and mentoring others to meet both their career goals and the organization goals

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