Data Scientist

Location

This position is onsite minimally 3 days a week at Jackson Service Center located in Jackson, MI. The selected candidate must be within a commutable distance or be willing to relocate (relocation package is available for those that qualify).

The Applications and Analytics team is at the heart of innovation, powering Michigan's future by crafting cutting‑edge digital solutions that transform how our customers and communities experience energy. Guided by our Digital First strategy, we harness modern technical practices and agile methodologies to ensure data and insights are accessible, reliable, and actionable, enabling evidence‑based decision‑making, operational efficiency, and innovation across the organization.

• 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.

• 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.

• Bachelor's degree in Information Technology, Data Analytics, or a related field, with two (2) or more years of experience in data science, data analysis, data modeling, and business needs assessment.
• [OR] Associate's degree in Data Science, Information Technology, Data Analysis, or a related field, with four (4) or more years of relevant experience.
• [OR] High School Diploma with six (6) or more years of experience in data science, data analysis, data modeling, and business needs assessment.

• Familiarity with dimensional modeling concepts (fact tables, dimensions, star schemas) and the rationale behind analytical data model structures.
• Proficiency in Python for data science and machine learning model development.
• Hands‑on experience using Databricks for large‑scale data science and experimentation.
• Working knowledge of Spark for distributed data processing and feature engineering.
• Experience applying statistical modeling, machine learning, or predictive analytics to business problems.
• Ability to collaborate with data engineers to design and prepare feature‑ready datasets and pipelines.
• Understanding of model evaluation, validation, and interpretability techniques.
• Experience communicating analytical results to stakeholders and supporting insight adoption.
• Strong understanding of the analytics lifecycle from problem definition through production support.

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

We, at CMS Energy, value Diversity, Equity, & Inclusion. It is part of our DNA. We treat our employees with respect, we treat each other fairly and we value the opinions of others. We are passionate about building and nurturing an environment where everyone feels included. We don't discriminate. We seek to learn about each other and better understand our unique…