Energy Data Analytics Strategist (Hybrid)

Southern California Edison; California (MO); Hybrid; USD 90,000 - 140,000; Full time

Job summary

Southern California Edison (SCE) invites you to join its data analytics team as an Advisor supporting Building Electrification and Income Qualified programs. You will apply advanced analytics, statistical modeling, and machine learning to drive program strategy, regulatory reporting, and operational decisions.

The role requires independent leadership of high‑impact analyses, governance of data quality, and collaboration with data scientists and stakeholders.

Qualifications

• Seven or more years of experience in data analysis.
• Experience using a variety of data tools and software.
• Bachelor’s degree in a relevant field.
• Experience using SQL, Python, SAS or similar.
• Experience developing predictive models or machine learning applications.

Responsibilities

• Gather data from databases, spreadsheets, APIs or data warehouses and ensure data integrity.
• Apply descriptive statistics, data mining, predictive modeling, and ML algorithms to identify patterns.
• Transform data into visual representations such as charts and dashboards for clear insights.
• Create reports with metrics, visuals, and actionable recommendations for non-technical audiences.
• Monitor data quality and analytics methodologies across projects.
• Collaborate with data scientists and business analysts to meet objectives.
• Protect sensitive data and ensure governance and integrity.

Skills

Data analysis

Data tools

Education

Bachelor's degree

Tools

SQL

Python

SAS

Job description

Southern California Edison (SCE) invites you to join its data analytics team as an Advisor supporting Building Electrification and Income Qualified programs. You will apply advanced analytics, statistical modeling, and machine learning to drive program strategy, regulatory reporting, and operational decisions.

The role requires independent leadership of high‑impact analyses, governance of data quality, and collaboration with data scientists and stakeholders.