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Load Forecasting Jobs in California (NOW HIRING)

Pravāh

ML Summer Intern

San Francisco, CA · On-site

$5K - $10K/mo

What You Might Work On Weather & Load Forecasting * Develop and improve forecasting models for weather and electricity demand * Working with large-scale weather foundation models, applying geo ...

JConnect Inc

Invent L3 Support

Los Angeles, CA

$17.25 - $23.25/hr

... ETL), SKU/store hierarchy mismatches, and promo/calendar ingestion errors. • Diagnose forecast variances: validate model inputs, analyze diagnostics, and recommend configuration or data ...

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How much do load forecasting jobs pay per hour?

As of May 30, 2026, the average hourly pay for load forecasting in California is $16.80, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $18.99 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Load Forecaster, and why are they important?

To thrive as a Load Forecaster, you need a strong background in mathematics, statistics, and energy systems, typically supported by a relevant degree such as engineering or applied mathematics. Proficiency with forecasting software, statistical analysis tools (like R or Python), and experience with SCADA or energy management systems is commonly required. Attention to detail, analytical thinking, and effective communication are standout soft skills for interpreting data and collaborating with cross-functional teams. These skills ensure accurate demand predictions, optimize resource allocation, and support reliable operation of power systems.

What are some of the common challenges faced by professionals in load forecasting roles, and how are they typically addressed?

Professionals in load forecasting often encounter challenges such as adapting to rapidly changing consumption patterns, integrating new data sources (like smart meters or renewable generation), and accounting for unexpected events (e.g., weather anomalies or economic shifts). These challenges are usually addressed by leveraging advanced statistical models, machine learning techniques, and close collaboration with data engineers and grid operators. Regularly updating models and ongoing training help ensure forecast accuracy, while teamwork facilitates the incorporation of real-time data and feedback.

What is load forecasting?

Load forecasting is the process of predicting the future demand for electricity over a specific period. Utilities and energy companies use load forecasting to ensure that they can meet customer demand efficiently and reliably. Accurate load forecasts help with planning generation, purchasing energy, managing grid stability, and optimizing operational costs. Forecasts can be short-term (hours or days), medium-term (weeks or months), or long-term (years), and they are crucial for maintaining a stable and economical power supply.

What is the difference between Load Forecasting vs Load Data Analyst?

AspectLoad ForecastingLoad Data Analyst
CredentialsBachelor's in Engineering, Data Science, or related fields; certifications in data analysis or energy managementBachelor's in Data Science, Statistics, or related fields; certifications in data analysis tools
Work EnvironmentEnergy companies, utilities, or grid operators; focus on predictive modelingData-driven roles in various industries; focus on analyzing and interpreting data
Industry UsagePrimarily in energy, utilities, and power sectors

Load Forecasting involves predicting future energy demand using statistical and machine learning models, essential for grid stability. Load Data Analysts focus on analyzing existing energy data to identify trends and support decision-making. While both roles require data analysis skills, Load Forecasting emphasizes predictive modeling specific to energy consumption, whereas Load Data Analysts interpret historical data to inform strategies.

What are popular job titles related to Load Forecasting jobs in California? For Load Forecasting jobs in California, the most frequently searched job titles are:
What job categories do people searching Load Forecasting jobs in California look for? The top searched job categories for Load Forecasting jobs in California are:
Load Forecasting jobs near you
Infographic showing various Load Forecasting job openings in California as of May 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $34,941 per year, or $16.8 per hour.

Staff Product Manager- Energy Intelligence Platform

Amperesand

San Francisco, CA • On-site

Full-time

Posted 12 days ago

Job description

Job Summary:
Amperesand is reinventing how the world powers its most critical systems. They are hiring a Staff Product Manager to build the Energy Intelligence Platform, which involves developing and launching an AI native control and monitoring platform that enhances power converters.
Responsibilities:
• Own the software roadmap and full product lifecycle for site level controls, monitoring, diagnostics, and customer integrations, from requirements through launch, adoption, and long term maintenance
• Define software strategy for how our site controllers interact with local customer systems and authorized cloud systems
• Apply AI and machine learning techniques to build predictive analytics, e.g., predictive maintenance, load forecasting, into the Energy Intelligence Platform
• Drive customer discovery and competitive analysis to identify unmet needs across utility, neo clouds and hyperscalers to set product direction and prioritize the roadmap
• Influence business strategy and product positioning via data backed customer insights for executive leadership
• Work directly with customers to drive alignment between software development and field performance needs, e.g., availability, latency, MTTR
• Track and report KPIs for system performance, platform stability, and user experience
• Be a subject matter expert, staying abreast of technical and business developments in distributed and grid connected asset controls and interfaces
Qualifications:
Required:
• 5+ years in a product function for industrial or energy software, control systems or software orchestrating distributed assets. Must have shipped major products or releases and have significant individual ownership
• Experience with one or more of: EMS, SCADA, DERMS, or grid edge control systems
• Familiarity with one or more industrial communication protocols, e.g., Modbus RTU TCP, DNP3, OPC UA, CAN, GOOSE, IEEE 2030.5
• Experience building with hardware software teams in complex, high reliability markets
• Excellent communication skills, able to bridge technical, customer, and business contexts
• Proficient user of AI agents, Jira, Git, Figma or equivalent, experience producing PRDs, integration guides, and release documentation
• Bachelor’s degree in Engineering, Computer Science, Physics, or a related field
Preferred:
• Understanding of deterministic control loops, fault tolerant design, and embedded cloud control handoffs, experience with Linux based edge devices, gateways, or PLCs
• Integration experience with inverters, BESS, relays, metering, site controller architectures, and local supervisory logic for microgrid or distributed energy control
• Experience defining requirements and managing integration with customer side EMS, SCADA, and building or battery management systems, exposure to IEC 61850, IEEE 2030.5, DNP3, or similar
• Knowledge of telemetry data structures, e.g., time series, events, alarms, ability to specify logging, diagnostics, and performance KPIs for distributed assets
• Hands on experience securing edge devices in the field, OTA update pipelines, software signing, OT IT segmentation, and remote fleet monitoring across distributed assets
• Experience applying machine learning to operational technology contexts, e.g., predictive maintenance, anomaly detection, load forecasting, or optimization of distributed energy assets
Company:
Amperesand operates as a grid infrastructure solution provider. Founded in 2023, the company is headquartered in Singapore, SGP, with a team of 11-50 employees. The company is currently Early Stage.

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