Data Scientist

Consumers Energy is seeking a Data Scientist to help strengthen the organization’s data output processes and turn business needs into practical analytical and strategic outcomes. In this hybrid role based in Michigan, you will partner with stakeholders to define requirements and then design, build, and maintain scalable analytics solutions, pipelines, models, and reporting.

This position focuses on end-to-end analytics lifecycle execution, from translating ambiguous business problems into structured approaches through production deployment, monitoring, and continuous improvement of decision-support tools.

Role focus

• Support Consumers Energy’s data output processes and collaborate with the business to define requirements for analytical and strategic initiatives.
• Design, develop, and maintain analytical solutions, pipelines, models, and reporting that deliver actionable insights for business execution.
• Lead analytics initiatives from ideation through production and adoption, with awareness of common analytics pitfalls.

Responsibilities

• Prioritize business initiatives and structure projects for optimal success, considering budget, staffing, and regulatory requirements.
• Communicate data science outputs effectively and support development of models and solutions that lead to clear, actionable insights.
• Plan, organize, and manage resources and processes to meet project or program objectives within scope, timelines, quality standards, and budget constraints.
• Design, develop, and maintain scalable analytical solutions using Python, SQL, Spark, Databricks, Microsoft Fabric, and cloud-based analytics platforms.
• Build and optimize enterprise data pipelines to extract, transform, and integrate data from multiple internal and external sources.
• Design and implement Lakehouse architectures, dimensional models, and curated data products for advanced analytics and reporting.
• Develop predictive, prescriptive, and machine learning models to identify trends, risks, opportunities, and future business outcomes.
• Independently handle data exploration, feature engineering, model development, validation, deployment, and monitoring.
• Translate ambiguous business problems into analytical frameworks, hypotheses, models, and actionable recommendations.
• Create complex business logic, algorithms, and statistical methodologies to support decision-making.
• Create, optimize, and maintain Power BI semantic models, dashboards, reports, KPIs, and data visualizations.
• Partner with business leaders to identify where analytics, machine learning, and AI can improve operational performance and business outcomes.
• Evaluate data quality, establish governance practices, and ensure analytical solutions maintain accuracy, scalability, and reliability.
• Present analytical findings and recommendations to technical and executive audiences.
• Support deployment, operationalization, and continuous improvement of analytical models and decision-support tools.
• Perform other duties as assigned or as necessary.

Requirements

• Strong quantitative analytics and structured problem solving skills.
• Ability to evaluate strengths and weaknesses of alternative solutions, conclusions, or approaches.
• Basic knowledge of data modeling, machine learning algorithms, statistical analysis, data visualization, and data engineering.
• Broad understanding of project management principles, including identifying project and business requirements.
• Excellent written and verbal communication skills, including the ability to compile, organize, interpret, and clearly communicate results.
• Strong process management skills and strong logic and reasoning abilities.
• Advanced proficiency in Python, SQL, R, PySpark, or similar analytical programming languages.
• Deep experience with Microsoft Fabric, Databricks, Azure Data Services, Data Lakehouse architectures, and enterprise data platforms.
• Strong understanding of data engineering concepts including ETL/ELT, data orchestration, pipeline development, and distributed data processing.
• Experience building semantic models and interactive dashboards using Power BI.
• Demonstrated expertise in predictive analytics, forecasting, statistical modeling, machine learning, and AI applications.
• Strong knowledge of dimensional data modeling, star schema design, data warehousing, and Lakehouse principles.
• Experience combining structured and unstructured data sources to create enterprise analytical solutions.
• Ability to independently lead analytics projects from business intake through production deployment.
• Strong critical thinking and problem solving, including translating business challenges into technical solutions.
• Ability to communicate complex technical concepts to non-technical stakeholders and executive leadership.

Technologies

• Python, SQL, Spark, Databricks, Microsoft Fabric, Power BI, R, PySpark, Azure Data Services
• Lakehouse architectures, ETL/ELT, Power BI semantic models

Location and work model

• Michigan, US (hybrid)
• Required onsite days: Monday, Tuesday, and Thursday.
• May be assigned to any Consumers Energy Service Center in Michigan’s lower Peninsula.
• Selected candidate must be within commutable distance or willing to relocate (relocation package available for those that qualify).
• Listed as multiple locations in MI, US.

Education and experience

• Minimum experience: 2 years.
• Education: Bachelor’s degree in Information Technology, Data Analytics, or a related field.

Benefits

• Competitive compensation packages
• Medical, Dental and Vision
• 401k with company match
• Paid parental leave
• Up to 13 paid Holidays
• Paid time off
• Educational Assistance Program

Immigration sponsorship

• This position is not eligible for immigration sponsorship (e.g., H-1B, TN, etc.).
• Unable to hire individuals with CPT, OPT, or STEM OPT for this position because it is not eligible for participation in the H-1B lottery program and is not eligible for current or future immigration sponsorship for a work visa.