Sr. Manager, Data Science/Reliability - Location Flexible

Requisition ID# 162793

Job Category: Compliance / Risk / Quality Assurance; Accounting / Finance; Business Operations / Strategy; Engineering / Science; Maintenance / Construction / Operations

Job Level: Senior Manager

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; 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 City

Position Summary:
This position reports to the Sr Director, System Performance, Reliability & Resilience Strategy and is responsible for the following:
* Developing predictive analytical models
* Just in time replacement
* Asset replacement prioritization
* Identifying trends and focus areas based on asset classes, regions, etc.
* Developing tools for engineering and operational usage to drive reliability

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.

A reasonable salary range is:

• Minimum Base Salary (Bay Area) $170,000.00
• Mid Base Salary (Bay Area) $230,000.00
• Maximum Base Salary (Bay Area) $290,000.00

• Minimum Base Salary (California) $162,000.00
• Mid Base Salary (California) $219,000.00
• Maximum Base Salary (California) $276,000.00

Job Responsibilities:
* Develops and builds high performing teams by setting goals, developing, and managing work resources, and ensuring the team has adequate tools, training, and technology to successfully deliver outcomes.
* Works with enterprise leaders to identify and solve complex business problems requiring the implementation of data science, machine learning and artificial intelligence.
* Ensures standards and processes are implemented to improve quality and timeliness of machine learning/artificial intelligence/optimization models.
* Develops and implements frameworks to validate models, methodologies, as well as communicate results.
* Acts as peer reviewer for complex code scripts and model development for broad scope projects. Reviews and approves the maturity for release of technical features in data science products.
* Conducts risk-evaluation studies on machine learning/artificial intelligence/optimization model impact of business outcomes. Assesses risk and maturity assessment of data science standards and tools.
* Participates in the community of practitioners that co-creates the development of data science, artificial intelligence, mathematical modeling and simulation, and similar emerging technologies to continuously assess their impact on business strategies
* Develops budget (expense, capital, and expenditures) and monitor, forecast and report on budget performance.

Qualifications:Demonstrated track record and understanding of data science and machine learning algorithms (supervised, unsupervised), ML domains (computer vision, NLP, etc.). The position requires the candidate to demonstrate a track record on data science, as the position will lead development of tools, automated processes to capture performance and provide predictive models to improve system performance. The team will manage large data sets and build automated tools for asset failure analytics, and other predictive models to improve system reliability.

Demonstrated track record in the following:
* Statistics: statistical modeling, experimental design, sampling, clustering, data reduction, confidence intervals, testing, modeling, predictive modeling and other related techniques. The position requires demonstrated experience in statistical analysis for power systems, it requires developing models to prevent unplanned outages and also tools to quantify benefits from various work across the system for reliability and resilience of the system. This position will lead the develop industry leading analytics for system performance and reliability functions across PG&E.

* Artificial Intelligence: machine learning, predictive analytics, as they collect, analyze and extract value out of data; simulation. The position will leverage emerging trends and technologies for artificial intelligence, machine learning and predictive analytics to create tools to surgically improve reliability performance. A demonstrated track record of these techniques is mandatory for the successful candidate for this position, along with the ability to perform complex power system simulations.

* Software Engineering: programming languages, big data wrangling packages, cloud services, APIs, and related tools. As the lead developer for the predictive reliability analytic tools, the candidate must be proficient in programming and have previous history in development of cutting edge and commercial grade tools for electric power systems.

* Seeing ahead to future possibilities and translating them into breakthrough strategies. As the PG&E lead on predictive analytics, the position requires the candidate to be an active industry participant with demonstrated track record in collaborating with research institutions and universities and others on breakthrough strategies and thinking. Ability to form and utilize partnerships will support the development of the breakthrough tools.

* Ability to clearly and concisely communicate and present complex analysis to both quantitative and non- quantitative audiences. The position requires explaining complex topics to various audiences, both internal and external. The findings from the analytical tools will drive investment decisions, that require a solid analytical foundation.
* Competency in planning and prioritizing work to meet commitments aligned with organizational goals. As the head of predictive analytics for reliability and system performance the work prioritization, project management and organizational skills are a necessity.

* Domain expertise: familiarity with one or more line of business (electric, customer, generation, procurement, gas, risk, etc.) and ability to identify areas where data science can improve processes and inform decision making (this may also include familiarity with the datasets/databases that support these lines of business). Position requires electric power system domain expertise combined with demonstrated data analytic capabilities within the domain. The position will have significant influence on company decision making by development and utilization of the complex analytical tools.

Minimum:
* Bachelor's degree in Statistics, Mathematics, Applied Science, Data Science, Engineering, Physics, Economics, or equivalent field or equivalent working experience
* 2 years hands-on experience in data science
* 4 years of leadership experience in data science

Desired:
* Advanced degree in Statistics, Mathematics, Applied Science, Data Science, Engineering, Physics, Economics, or equivalent field.
* Utility industry experience: 5 years

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