Principal, Data Scientist (Flexible location)

Requisition ID # 166542 

Job Category: Accounting / Finance 

Job Level: Manager/Principal

Business Unit: Operations - Other

Work Type: Hybrid

Job Location: Dublin

Position Summary

Designs, develops, and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating for defensible, valid, scalable, reproducible, and documented machine learning and artificial intelligence models (predictive or optimization) for problem-solving and strategy development. Participates in internal and external communities of practice in data science/artificial intelligence/machine learning to advance knowledge in the field. Educates the non-technical community on advantages, risks, and maturity levels of data science solutions.

This position is hybrid. You will work from your remote office and your assigned location based on business needs. The headquarters location is flexible 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, collective bargaining agreements, and internal equity. Although we estimate that 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, taking into account these factors.

A reasonable salary range is:
Bay Area Minimum: $159,000
Bay Area Maximum: $271,000
&/OR
California Minimum: $151,000
California Maximum: $257,000

This job is also eligible for participation 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. 
•    Process and analyze large scale remote sensing and GIS datasets via advanced geospatial algorithms and models.
•    Applies and evaluates data science, machine learning, and 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 machine learning algorithms for solving business problems.
•    Mentors junior data scientists and drives standardization in processes and toolsets across the data science community at PG&E. 
•    Collaborates with analytics platform owners to prioritize and drive the development of scalable data science capabilities.
•    Acts as a peer reviewer for complex models and AI algorithm proposals.
•    Recognizes and prioritizes the most critical work related to data science models to achieve the highest operational and strategic impact for analytics in the business.
•    Works with enterprise leaders as an advocate for the 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, Economics, Engineering, Mathematics, Applied Sciences, Statistics, or an equivalent field.
•    8 years in data science (or 2 years if you possess a 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 geospatial algorithms and GIS data transformation and processing
•    Bonus if you have experience with Pyspark and geospatial libraries like Sedona and raster