Consumers Energy is Michigan's largest energy provider, providing natural gas and/or electricity to 6.8 million of the state's 10 million residents in all 68 Lower Peninsula counties. Consumers Energy knows job number one is to keep the lights on for customers. We are committed to delivering reliable, clean, and affordable energy to our customers 24/7. This position is not eligible for immigration sponsorship, e.g., H-1B, TN, etc. Please do not apply if you will need immigration sponsorship for a work visa now or in the future, including sponsorship for H-1B, TN, etc., now or in the future. We are unable to hire individuals with CPT, OPT, or

STEM OPT

for this position as the position 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.

Location:

This is a hybrid (virtual/onsite) position with required onsite days on Monday, Tuesday and Thursday and may be assigned to any Consumers Energy Service Center located throughout Michigan's lower Peninsula. The selected candidate must be within a commutable distance or willing to relocate (relocation package is available for those that qualify). General Summary of Job Responsibilities The Data Scientist will support the organization's data output processes and partner with the business to define requirements for analytical and strategic initiatives. This role requires a strong understanding of business needs and the ability to generate actionable insights using a variety of analytical methods. Essential Duties and Responsibilities Prioritize business initiatives and structure projects for optimal success, considering budget, staffing, and regulatory requirements.

Communicate data science outputs effectively and support the development of models and solutions that provide clear, actionable insights for business execution.

Plan, organize, and manage resources and processes to achieve project or program objectives within established scope, timelines, quality standards, and budget constraints.

Lead analytics initiatives from ideation through production and adoption, demonstrating a strong understanding of the analytics lifecycle and common pitfalls.

Perform other duties as assigned or as necessary. Additional Essential Duties and Responsibilities 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 that extract, transform, and integrate data from multiple internal and external sources.

Design and implement Lakehouse architectures, dimensional models, and curated data products to support advanced analytics and reporting.

Develop predictive, prescriptive, and machine learning models to identify trends, risks, opportunities, and future business outcomes.

Independently perform data exploration, feature engineering, model development, validation, deployment, and monitoring.

Translate ambiguous business problems into analytical frameworks, hypotheses, models, and actionable recommendations.

Develop 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 opportunities 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 both technical and executive audiences.

Support the deployment, operationalization, and continuous improvement of analytical models and decision-support tools. Knowledge/Skills/Abilities Strong quantitative analytics skills and structured problem solving abilities.

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 and ability to identify project and business requirements.

Excellent written and verbal communication skills.

Ability to compile, organize, interpret, and clearly communicate data and analytical results.

Strong process management skills.

Ability to use logic and reasoning to evaluate alternative solutions, conclusions, or approaches. Additional Knowledge/Skills/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 skills with the ability to translate business challenges into technical solutions.

Ability to communicate complex... For full info follow application link. All qualified applicants will not be discriminated against and will receive consideration for employment without regard to protected veteran status, disability, race, color, religion, sex, sexual orientation, gender identity or national origin.