Hybrid Data Scientist — Energy Analytics & ML

Consumers Energy; Michigan; Hybrid; USD 85,000 - 125,000; Full time

Benefits offered by this job

Medical, Dental and Vision

401k with company match

Paid parental leave

Up to 13 paid Holidays

Paid time off

Educational Assistance Program

Job summary

Consumers Energy is hiring a Data Scientist to support data output processes and partner with the business to define analytical requirements. The role involves delivering insights using various analytical methods and leading analytics initiatives from ideation through production.

You will design data pipelines, build Lakehouse architectures, and develop predictive models while collaborating with leadership to improve operational performance.

Qualifications

• Bachelor’s degree in Information Technology, Data Analytics, or related field with 2+ years in data science/analysis
• Alternative: Associate’s degree with 4+ years relevant experience
• Alternative: High School Diploma with 6+ years relevant experience

Responsibilities

• Translate business needs into analytical requirements and actionable insights
• Lead analytics initiatives from ideation to production and adoption
• Develop predictive and prescriptive models to inform decisions
• Design scalable data pipelines and lakehouse architectures
• Create dashboards and semantic models in Power BI
• Evaluate data quality and establish governance practices

Skills

Quantitative analytics

Data visualization

Communication

Project management

Critical thinking

Problem solving

Team collaboration

Business understanding

Education

Bachelor's in IT/Data Analytics

Associate’s in Data Science/IT

High School Diploma +6 yrs exp

Tools

Python

SQL

Spark

Databricks

Microsoft Fabric

Power BI

Job description

Consumers Energy is hiring a Data Scientist to support data output processes and partner with the business to define analytical requirements. The role involves delivering insights using various analytical methods and leading analytics initiatives from ideation through production.

You will design data pipelines, build Lakehouse architectures, and develop predictive models while collaborating with leadership to improve operational performance.