Description
Job ID: 17374
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:
- U.S. Master's degree or foreign equivalent in Data Science, Statistics, or a closely related field
- Intermediate to advanced proficiency in data modeling, data structures, and complex SQL querying across large, multi-source datasets
- Experience working with relational and enterprise data platforms, including SAP IS-U, SAP BW, SAP Analysis, Oracle Database, SQL Server, and related tools such as Alteryx, Azure ML, Power BI, Metrics IDR, and Microsoft 365
- Experience in quantitative analytics and statistical modeling, including data mining, regression analysis, hypothesis testing, predictive modeling, multivariate analysis, and model optimization
- Experience with machine learning and applied analytics, including feature engineering, supervised and unsupervised learning, model training, and optimization, with familiarity in modern AI approaches such as RAG and LLM workflows
- Intermediate to advanced proficiency in data engineering and analytics, including designing, building, and maintaining scalable data pipelines and data architectures (ETL/ELT), as well as integrating and transforming large, multi-source datasets using tools such as SQL, Python, PySpark, Azure Databricks, and REST APIs
Other Requirements:
- Demonstrated ability to translate business questions into analytical approaches, determine appropriate methodologies, and communicate complex technical concepts, analytical findings, and data-driven recommendations effectively to both technical and non-technical audiences
- Self-starter with the ability to quickly learn and apply new technologies, analytical frameworks, and business processes, while contributing to the advancement of team knowledge, capabilities, and best practices
- Strong interpersonal, analytical, and problem-solving skills, with the ability to work independently and collaboratively in support of complex business and analytical objectives
Contact
DTE Energy
2000 2nd Ave
Detroit
Michigan United States
www.dteenergy.com
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