Manager, Data Solutions | PG&E

Job title: Manager, Data Solutions

Company: PG&E

Job description: Requisition ID # 161283Job Category: Accounting / FinanceJob Level: Manager/PrincipalBusiness Unit: Operations – OtherWork Type: HybridJob Location: Oakland; Alameda; Alta; American Canyon; Angels Camp; Antioch; Auberry; Auburn; Avenal; Avila Beach; Bakersfield; Balch Camp; 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; Watsonville; West Sacramento; Wheatland; Whitmore; Willits; Willow Creek; Willows; Windsor; Winters; Woodland; Yuba CityDepartment OverviewThe aim of the Wildfire Data Solutions team in the Wildfire Risk Management organization is to enhance the risk practices of PG&E’s Electric Operation business and thereby address changing external conditions such as climate change. To this end the Widlfire Data Solutions team develops and maintains key data sets and productionalizes predictive models to enable PG&E to close the gap between metrics and electric system performance. These models provide a multi-layered view of risk across the electric system so that decision-making processes include and empower employees at all levels of the company to manage risk appropriately.Sample activities include:

Development and curation of remote sensing meteorological and asset health data pipelines to support the development of prediction of electric distribution equipment failure before it occurs.
Development and productionalization of supervised and unsupervised machine learning models using Python and executed in Foundry or AWS
Interpretation and representation of data in models that combine a range of data sources such as the electric system asset data, vegetation, and meteorology.

Position SummaryPG&E is looking for a Manager to lead the Wildfire Data Solutions team within the Wildfire Risk Management department. This team lead will primarily be focused on developing the critical data sets that drive the predictive models that quantify wildfire risk along the electric grid. In this role the successful candidate will be uniquely positioned at the forefront of utility industry analytics and have the opportunity to advance PG&E’s triple bottom line of serving the people of our hometowns, the planet and the long-term prosperity of the state of California. 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 will 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&/ORCA Minimum: $151,000
CA Maximum: $257,000This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.Job Responsibilities

Develop and implement an ongoing Risk product strategy toward the company stand that catastrophic wildfire shall stop.
Set performance targets and working practices within the team to ensure work meets high-quality Data Science standards.
Represent and lead the development of communication model results to the broader PG&E data science and Electric community.
Work with Wildfire and Electric Senior Leadership to first identify strategic issues, define a successful project outline, and then lead the delivery of this work.
Manages staff to accomplish results through effective recruitment and selection, training and development, performance management and coaching, and rewards and recognition.
Utilizes deep understanding of business drivers and financial levers, along with instrumental data science techniques, to prioritize work and provide strategic decision support.
Works with enterprise leaders as an advocate for digital transformation of the business through the adoption of data science, artificial intelligence, and data-driven business processes.
Acts as peer reviewer for code scripts and model development for narrow scope projects. Reviews and approves the maturity for release of technical features in data science products.
Supervises the technical development of mathematical models and AI simulations which represent complex business scenarios through formulas and data science code for problem-solving.
Conducts risk evaluation studies of model impact on business outcomes.
Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
Monitors the development of data science, machine learning, artificial intelligence, mathematical modeling and optimization, and similar emerging technologies to continuously assess their impact on business strategies. Participates with peers in risk and maturity assessment of data science tools.

QualificationsMinimum:

Bachelor’s degree in Statistics, Mathematics, Applied Science, Data Science, Engineering, Physics, Economics, or equivalent field.
Experience in Data Science, 2 years OR Masters Degree in Data Science, Machine Learning
Leadership experience in Data Science, 2 years

Desired:

Doctorate Degree in Data Science, Machine Learning, or job-related discipline or equivalent experience
Utility industry experience, electric or gas, or other job-related, 3 years
Leadership qualities: detail oriented, curious, thoughtful and asks good questions, ownership of work, collaborative and communicative, comfortable working cross-functionally
Knowledge of data model design philosophies and methodologies
Ability to solve simple and complex problems involving arithmetic as needed to perform at the job level
Ability to develop reports, models, and simulations as needed to perform at the job level with dashboarding tools such as PowerBI, streamlit, Foundry Workshop
Knowledge of project management theories, concepts, methods, best practices, and techniques as needed to perform at the job level
Knowledge of statistical theories, concepts, methods, best practices, and analyses as needed to perform at the job level
Knowledge of relevant programming languages and platforms, ie AWS S3, SageMaker, Foundry, Snowflake, PySpark, SQL, Python
Knowledge of Spark, parallel processing, and distributed computing.
Experience with large unstructured geospatial datasets such as rasters, satellite imagery, lidar
Experience with data acquisition, querying, data integration, spatial indexing, storage, data structures
Expertise in efficient storage & querying, optimization of pipelines for compute & memory