DTE is one of the nation’s largest diversified energy companies. Our electric and gas companies have fueled our customer’s homes and Michigan’s progress for more than a century. And as Michigan’s largest source of renewable energy, we’re creating a cleaner, healthier environment to power our future. We’re also serving communities beyond Michigan, where our affiliated businesses offer renewable energy, emission control technologies, and energy services to industries in 19 states.
But we’re more than a leading energy company… and working at DTE is more than just a job. At DTE, we take great care of each other and our customers, and we use our energy to be a force for growth and prosperity in our communities. When you join us, you’ll be part of a team that welcomes, recognizes, and celebrates differences and values everyone’s health, safety, and wellbeing. Are you ready to make that kind of difference? Bring your energy to DTE. Together, we can achieve great things.
Testing Required: Not Applicable
Hybrid Role: Must be able to come on-site periodically and reside a commutable distance from the assigned work location.
Emergency Response: Yes – Must be available to perform a primary assignment in support of DTE’s emergency response to storms or other events that impact service to our customers.

JOB SUMMARY

Leads large business unit or enterprise-level analytics projects with broad responsibilities for translating business requirements into analytical constructs and providing analytical insights for effective decision making. Mentors less experienced team members to run analytical experiments in a methodical manner, evaluates alternative approaches and develops predictive models to forecast business performance metrics. Communicates effectively to technical and non-technical stakeholders with strong domain expertise and business acumen. Additionally, this role requires researching and recommending new technologies and best practices within the industry to develop the organization’s analytics strategies and roadmap.

KEY ACCOUNTABILITIES

• Leads analytics projects and collaborates with cross-functional stakeholders to complete end-to-end analyses that includes business requirements, data gathering, analysis, scaleable solutions, and presentations
• Conducts advanced statistical analysis to determine trends and significant data relationships, and proactively recommend areas of improvement.
• Develops complex data sets and predictive models to support key decisions to improve safety, employee engagement, operation efficiency, product quality, and customer satisfaction
• Prepares and delivers insightful presentations and actionable recommendations. Educates leaders and other employees on complex analytical findings in basic terms with storytelling and data visualization
• Identifies and evaluates technologies and provides strategic inputs to advance the organization’s analytics capabilities
• Implements new statistical, mathematical, machine learning, or other methodologies for modeling or analyses
• Responsible for discovering insights from Big Data to help shape or meet specific business needs and goals.
• Utilizes business expertise to translate goals into data-based deliverables, such as predictive models, pattern detection analysis or optimization algorithms
• Champions self-service reporting capability and use of Business Intelligence and statistical tools; advances the analytical capabilities of the organization
• Develops data and analytical processes based on Continuous Improvement learnings and practices

MINIMUM EDUCATION & EXPERIENCE REQUIREMENTS

This is a dual-track base requirement job; education and experience requirements can be satisfied through one of the following three options:

• Bachelor’s degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational Psychology and Econometrics, etc.) and 6 years of experience working in a data analytical or computer programming function; or
• Master’s degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational Psychology and Econometrics, etc.) and 4 years of experience working in a data analytical or computer programming function
• PhD degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational Psychology and Econometrics, etc.) and 2 years of experience working in a data analytical or computer programming function

OTHER QUALIFICATIONS

Preferred:

• PhD degree in Data Science
• Experience in quantitative analytics (e.g., data mining, regression analysis, hypothesis testing, predictive modeling and model optimization)
• Intermediate- to advanced-level knowledge and skills in data modeling, data structure, and the application of complex SQL queries with data from multiple sources, including Big Data platforms (e.g., Hadoop, AWS, Azure, Databricks)
• Experience with SAP Business Intelligence tools and SAP CRM, ISU, and BW data
• Intermediate-level or higher Continuous Improvement knowledge, skills, and certifications
• Strong written and verbal communication skills
• Strong business acumen and utility/energy industry experience

Other Requirements:

• Intermediate- to advanced-level skills and experience with data mining and statistical analysis using analytical packages / tools (e.g., R, SAS, SPSS, Stata, MATLAB, Minitab, etc.)
• Intermediate- to advanced-level skills and experience articulating business questions, pulling data from relational databases (e.g., SAP BW, ORACLE, SQL SERVER) and using advanced excel and statistical tools (e.g., Minitab, Alteryx, Advanced Excel with VBA, R, SAS, SPSS, Stata, MATLAB, etc.) and determining the appropriate analytical approach to conduct in-depth analysis to support decision making
• Intermediate- to advanced-level programming skills in SQL, C/C++/C#, Java, R, Python, PHP, ASP, or SAS
• Intermediate- to advanced-level skills in applied research design and machine learning (e.g., multivariate statistical analysis, unsupervised and supervised learning, predictive modeling, etc.)
• Self-starter and quick learner; advances self and others’ knowledge and skill sets in business processes, data science, new analytical frameworks, technologies, and applications
• Strong interpersonal, analytical and problem-solving skills, including ability to communicate technical information and complex data analytics to a non-technical audience

Please refer the Job description for details