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From Home Predictive Analytics Jobs in California

S., country-specific location are expected to work from the office at least four days per week ... statistics predictive analytics, research) * OR Master's Degree in Statistics, Econometrics ...

S., country-specific location are expected to work from the office at least four days per week ... predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science ...

General Information

Los Angeles, CA · On-site

$50 - $80/hr

The role focuses on predictive analytics and all-hazards risk modeling-including wildfire, extreme ... From strategy through delivery, our agile teams across 52 offices in 12 countries partner with ...

Statistics/decision science, predictive analytics, or test-and-learn measurement experience ... At Synchrony, our way of working allows you to have the option to work from home near one of our ...

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From Home Predictive Analytics information

Is 40 too late for data science?

For a role like from home predictive analytics, age is not a barrier; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, regardless of age. Continuous learning and practical experience are key to entering the field at any age.

How can I make $100,000 a year working from home?

A from home predictive analytics professional can reach a $100,000 annual income by gaining advanced skills in data analysis, machine learning, and programming languages like Python or R, along with relevant certifications. Building a strong portfolio, gaining experience, and working with high-paying clients or companies can also help achieve this income level.

Can you work from home doing data analytics?

Yes, many data analytics roles, including those in predictive analytics, can be performed remotely. These jobs typically require skills in data analysis tools, programming languages, and strong communication, and often involve using cloud-based platforms and collaboration tools to work effectively from home.

What is the difference between From Home Predictive Analytics vs Data Analyst?

AspectFrom Home Predictive AnalyticsData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related field; proficiency in analytics toolsBachelor's in Statistics, Mathematics, or related field; strong analytical skills
Work EnvironmentRemote, home-based role with flexible hoursTypically office-based, but remote options are common
Industry UsageUsed across tech, finance, marketing for predictive modelingUsed in various industries for data interpretation and reporting
Common Search/ComparisonOften compared for roles involving predictive modeling from homeCompared for data interpretation roles in analytics

From Home Predictive Analytics focuses on building models to forecast future trends remotely, requiring skills in machine learning and statistical modeling. Data Analysts interpret existing data to generate reports and insights, often with less emphasis on predictive modeling. Both roles may overlap but differ mainly in their focus on prediction versus analysis and work environment.

How to make 2000 a week working from home?

A From Home Predictive Analytics role can potentially earn $2000 or more weekly by working on high-demand projects, utilizing skills in data analysis, machine learning, and statistical modeling. Achieving this income level typically requires advanced expertise, a strong portfolio, and the ability to secure multiple clients or projects simultaneously, often through freelance platforms or direct contracts.
What are the most commonly searched types of Predictive Analytics jobs in California? The most popular types of Predictive Analytics jobs in California are:
Infographic showing various From Home Predictive Analytics job openings in California as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.

Data Scientist - Predictive Analytics, Senior

Pacific Gas and Electric Company

Oakland, CA • Hybrid

Other

Posted 2 days ago

New


Pacific Gas and Electric Company rating

9.0

Company rating: 9.0 out of 10

Based on 46 frontline employees who took The Breakroom Quiz

3rd of 53 rated energy and utility


Job description

Requisition ID # 167320 

Job Category: Accounting / Finance 

Job Level: Individual Contributor

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; 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 Senior Manager of Reliability Analytics and is responsible for developing advanced data science models and industry-leading anomaly detection techniques to identify potential failures and enhance the reliability of the electric transmission and distribution grid. 

Key responsibilities include designing, developing, and executing scripts, programs, models, algorithms, and processes using structured and unstructured data from diverse sources and of varying sizes. The goal is to generate defensible, valid, scalable, reproducible, and well-documented machine learning and artificial intelligence models (predictive or optimization) to support problem-solving and strategic decision-making.

The role also involves active participation in internal and external communities of practice in data science, AI, and machine learning to stay current and contribute to advancements in the field. Additionally, the candidate will help educate non-technical stakeholders on the benefits, limitations, and maturity of data science solutions.

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, technologists, 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. Position requires reporting to Oakland/Dublin twice a week. 

PG&E is providing the salary range that can reasonably be expected for this position at the time of the job posting. This salary 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, internal equity, specific skills, education, licenses or certifications, experience, market value, and geographic location. The decision will be made on a case-by-case basis related to these factors. This job is also eligible to participate in PG&E's discretionary incentive compensation programs.  

Bay Area -  $126,000 - 179,300

&/OR

California: $120,000 - 170,500

Job Responsibilities

  • Lead research and development of state-of-the-art methodologies to detect potential system failures and improve the reliability of the electric transmission and distribution grid.
  • Applies data science/ machine learning /artificial intelligence methods to develop scalable, defensible and reproducible models, 
  • Serves as the technical lead for the development of predictive/reliability analytics models.
  • Develops python codes for data processing and data science model developments (e.g., ML/AI models, advanced statistical models)
  • Documents datasets, modeling processes, and result to ensure transparency, reproducibility, and defensibility. 
  • Contribute to the development of data science strategies aligned with system performance, reliability, and resiliency team goals.
  • Communicate technical concepts and model results to internal/external stakeholders. 

Qualifications

Minimum:

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

Desired:

  • Ph.D. or Master's degree in Electrical Engineering, Mechanical Engineering, Operations Research, Transportation Engineering, Physics, Applied Sciences, Statistics, or a related field. 
  • Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
  • Strong foundation in statistics, machine learning (ML), and artificial intelligence (AI).
  • Hands-on and theoretical experience in developing and deploying data science and ML models using Python.
  • Proven ability to formulate and solve unstructured, complex problems using data-driven approaches.
  • Proficiency in working with large datasets, including structured and unstructured data from diverse sources.
  • Excellent communication skills, with the ability to explain technical concepts to non-technical audiences.
  • Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies

What Pacific Gas and Electric Company employees say

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