Associate Data Scientist — Energy Analytics and Insights

Xcel Energy Inc; Minneapolis (MN); On-site; USD 85,000 - 121,000; Full time

Benefits offered by this job

Annual Incentive Program

Medical/Pharmacy Plan

Dental

Vision

Life Insurance

Pension

401(k) plan

Paid time off

Holidays

Tuition reimbursement

Transit programs

Job summary

Xcel Energy is seeking an Associate Data Scientist to analyze large datasets, apply statistical methods, and build predictive models that inform business decisions. You will collaborate with cross-functional teams to translate data insights into actionable strategies and help automate data collection while maintaining data integrity.

The role emphasizes communicating complex findings to non-technical stakeholders and contributing to reusable data tools and analytics workflows.

Qualifications

• Bachelor's degree in CS, data science, statistics, math or related analytical field.
• Experience with analytics methods and data-driven decision making.

Responsibilities

• Handle and analyze large datasets using statistical methods and ML algorithms.
• Collaborate with cross-functional teams to translate data findings into business strategy.
• Develop predictive models and automate data collection while ensuring data quality.
• Communicate findings clearly to non-technical stakeholders and business users.
• Support data-driven decision making and create reusable data products.

Skills

SQL

Python

Data analysis

Stakeholder communication

Education

Bachelor’s degree in computer science, data science, statistics, math or related analytical field

Tools

Power BI

Posit

Job description

Xcel Energy is seeking an Associate Data Scientist to analyze large datasets, apply statistical methods, and build predictive models that inform business decisions. You will collaborate with cross-functional teams to translate data insights into actionable strategies and help automate data collection while maintaining data integrity.

The role emphasizes communicating complex findings to non-technical stakeholders and contributing to reusable data tools and analytics workflows.