Data Scientist

Consumers Energy•Jackson, MI

3d•Hybrid

About The Position

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. Join a dynamic team where collaboration, creativity, and impact converge! We partner closely with business teams to uncover digital opportunities, prioritize high-impact outcomes, and deliver trustworthy, user-friendly technology. By embracing our CE Way principles—engaging on solutions, illuminating priorities, and minimizing waste—we build systems that are simple, helpful, and valuable. If you’re passionate about innovation, community, and shaping a sustainable energy future, come grow with us at Consumers Energy! 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.

Requirements

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.

Nice To Haves

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.
Handson experience using Databricks for largescale 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 featureready 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.

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.