Senior Data Scientist
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
Employment Sponsorship: This position is not eligible for visa sponsorship currently.
Hybrid Role: This role is hybrid, with an established schedule of in-person work required at an assigned work location. Any remote work is expected to be performed from an employee’s primary residence, unless allowed (or prohibited) through the Company’s remote work guidelines.
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:
- 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
Additional Information
Incumbents may engage in all or some combination of the activities and accountabilities, and utilize a variety of the competencies cited in this description depending upon the organization and role to which they are assigned. This description is intended to describe the general nature and level of work performed by incumbents in this job. It is not intended as an all-inclusive list of accountabilities or responsibilities, nor is it intended to limit the rights of supervisors or management representatives to assign, direct and control the work of employees under their supervision.
At DTE Energy, we are committed to providing an inclusive workplace where everyone feels welcome and a sense of belonging. We seek individuals with a heart for service, a passion to help our communities prosper, and ideas to help shape the future of energy. We are proud to be an equal opportunity, employer that considers all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, age, religion, disability, national origin, citizenship, height, weight, genetic information, marital status, pregnancy, protected veteran status or any other status protected by applicable federal and/or state laws.
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