Energy Data Analyst: Forecasting & Risk (Hybrid)

Clean Energy Alliance; Carlsbad (CA); Hybrid; USD 98,000 - 164,000; Full time

Benefits offered by this job

Health benefits

Disability insurance

Technology allowance

401(a) employer contribution

Paid vacation

Paid holidays

Job summary

Clean Energy Alliance seeks an Energy Data Analyst to join a growing team transitioning from startup-like operations to a long-term clean energy provider. The role reports to the Power Procurement Senior Manager and Energy Analytics and Risk Manager, collaborating with the Finance department.

The ideal candidate excels at data extraction, analytics, Excel modeling, and programming (Python/R/Stata). Knowledge of CAISO, CPUC, CEC, and DOE regulations is valued.

Qualifications

• Requires a bachelor’s degree in business, economics, data analytics, accounting or related field.
• Up to two years of experience related to energy markets and risk analytics.

Responsibilities

• Energy and Risk Analytics.
• Maintain and augment forecasting models for energy procurement and compliance requirements (hedges, RPS, resource adequacy).
• Modify and operate systems for measuring, monitoring, and reporting financial risk from power supply positions.
• Analyze risk management and performance of operating contracts.
• Manage cost of energy models.
• Calculate Value at Risk, Mark to Market, Gross Margin at Risk, PPA valuation and other risk metrics.
• Interact with third‑party energy technology providers.
• Contribute to routine production and dissemination of risk metrics and controls.

Skills

Excel modeling

Python

R

Stata

SQL

Education

Bachelor’s degree in business, economics, data analytics, accounting or related field

Tools

Power BI

Tableau

Job description

Clean Energy Alliance seeks an Energy Data Analyst to join a growing team transitioning from startup-like operations to a long-term clean energy provider. The role reports to the Power Procurement Senior Manager and Energy Analytics and Risk Manager, collaborating with the Finance department.

The ideal candidate excels at data extraction, analytics, Excel modeling, and programming (Python/R/Stata). Knowledge of CAISO, CPUC, CEC, and DOE regulations is valued.