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Load Forecasting Jobs (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 ...

MWResource

EMS Applications Engineer

Taylor, TX · On-site

$60 - $95/hr

... Load Forecasting, Operator Training Simulator (OTS) etc. Actively involved in the design, development, testing, validation and implementation of modifications and enhancements to EMS applications.

MWResource, Inc.

EMS Applications Engineer

Taylor, TX · On-site

$60 - $95/hr

... Load Forecasting, Operator Training Simulator (OTS) etc. Actively involved in the design, development, testing, validation and implementation of modifications and enhancements to EMS applications.

MWResource, Inc.

EMS Applications Engineer

Taylor, TX · On-site

$60 - $95/hr

... Load Forecasting, Operator Training Simulator (OTS) etc. Actively involved in the design, development, testing, validation and implementation of modifications and enhancements to EMS applications.

MWResource, Inc.

EMS Applications Engineer

Taylor, TX

$60 - $95/hr

... Load Forecasting, Operator Training Simulator (OTS) etc. Actively involved in the design, development, testing, validation and implementation of modifications and enhancements to EMS applications.

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Load Forecasting information

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$12

$17

$20

How much do load forecasting jobs pay per hour?

As of May 30, 2026, the average hourly pay for load forecasting in the United States is $17.02, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 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.

More about Load Forecasting jobs
What states have the most Load Forecasting jobs? States with the most job openings for Load Forecasting jobs include:
What job categories do people searching Load Forecasting jobs look for? The top searched job categories for Load Forecasting jobs are:
Load Forecasting jobs near you
Infographic showing various Load Forecasting job openings in the United States as of May 2026, with employment types broken down into 83% Full Time, 14% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $35,405 per year, or $17 per hour.
Senior Data Scientist (Python/R, ML, MLOps)

Senior Data Scientist (Python/R, ML, MLOps)

Computer Enterprises, Inc.

Richmond, VA • On-site

$60/hr

Other

Medical, Dental, Vision, Retirement

Posted 12 days ago

Job description

Data Scientist 

Job at a Glance 

  • Title: Data Scientist 

  • Location: Richmond, VA 

  • Contract: W2 only, 12-month contract with potential for extension or conversion  

  • Pay: $60/hour + optional medical, dental, vision, 401(k) match 

Overview 

This role serves as a technical consultant and senior individual contributor within our client''s Enterprise Data Analytics team, delivering advanced analytics and data science solutions that support operational reliability, grid modernization, customer experience, and clean energy initiatives. The position involves partnering with various business units to identify high-value data science use cases and deploying models to support asset health, load forecasting, outage prediction, grid resilience, and customer behavior analysis. 

Key Responsibilities 

  • Partner with business units such as Generation, Transmission & Distribution, Grid Operations, Asset Management, Customer Operations, and Finance to identify high value data science use cases. 

  • Design, build, and deploy predictive, prescriptive, and diagnostic models to support: Asset health and predictive maintenance, Load forecasting and demand modeling, Outage prediction, restoration optimization, and reliability analytics, Grid resilience, renewable integration, and emissions reduction initiatives, Customer behavior, billing, and energy efficiency programs. 

  • Apply advanced techniques such as time series forecasting, survival analysis, optimization, clustering, NLP, and anomaly detection to utility scale data. 

  • Develop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoring. 

  • Support implementation of MLOps best practices to ensure scalable, reliable, and auditable analytics solutions in compliance with enterprise and regulatory standards. 

  • Collaborate closely with data engineers, platform teams, and cloud architects to ensure models are production ready and performant. 

  • Build reusable analytical frameworks and accelerators that improve time to value across the Enterprise Analytics portfolio. 

  • Create intuitive visualizations, dashboards, and self-service analytics tools that empower stakeholders to explore insights independently. 

  • Mentor junior data scientists and analysts, contributing to analytics standards, code quality, and best practices. 

  • Support a commitment to safety, reliability, affordability, and clean energy transformation through responsible and ethical use of data and AI. 

Required Skills 

  • MUST have prior hands on experience as a Data Scientist on a project using Python or R. 

  • Proven ability to translate complex analytical findings into clear, actionable insights for business leaders, engineers, operations teams, and executives. 

  • Ability to create clear, interpretable visualizations that tell a compelling story, support decision making, and align with executive level messaging. 

  • Demonstrated experience creating interactive dashboards, reports, and applications (e.g., RShiny, Power BI, Streamlit, Dash) for business consumption. 

  • Strong experience working with structured, semi structured, and unstructured data (e.g., sensor/SCADA data, time series data, text, image). 

  • Working knowledge of MLOps practices including model development lifecycle management, automated testing, CI/CD pipelines, version control, and deployment (e.g., MLflow, Dataiku, Azure ML, or similar tools). 

  • Strong understanding of model monitoring, including performance tracking, explainability, bias detection, model drift, and reproducibility in production environments. 

  • Working knowledge of data engineering concepts, including data ingestion, transformation, feature engineering, and data quality controls. 

  • Experience with cloud and modern analytics platforms (AWS, Azure, GCP, Snowflake, Databricks, or similar) is a strong plus. 

  • Understanding of governance, security, and regulatory requirements for enterprise and utility data environments is preferred. 

  • Strong communication skills both verbal and written. 

  • Ability to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teams. 

  • Education: Bachelors or higher required 

  • Discipline: Computer Science, Information Systems, Mathematics 

Preferred Skills 

  • Understanding and/or Experience with data engineering is a plus. 

  • Experience with cloud technologies (AWS, Azure, GCP, Snowflake) is big plus. 

Why Should I Apply? 

This position offers the opportunity to work on impactful projects within a leading utility company, leveraging advanced data science techniques to support critical infrastructure and energy initiatives. Join a team committed to innovation, safety, and sustainability. 

About CEI: 

As a trusted technology partner, CEI delivers solutions that help our customers transform their business and achieve meaningful results. From strategy and custom application development through application management - our technology and digital experience services are tailored to meet each unique need of our customers. Our staffing solutions bring specialized skills to complement our customers'' workforce and project requirements. 

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