Associate Data Analyst
Detroit, Wayne County, Michigan, 48228, USA
Listed on 2026-07-01
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IT/Tech
Data Analyst, Data Scientist, Data Science Manager
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
Location: Coolidge Service Center
- Detroit MI
Hybrid Role: This role is hybrid, with an established schedule of in-person work required at Coolidge Service Center. 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.
Entry level job responsible for collecting, reviewing, validating and structuring business data for interpretation. Performs statistical predictive analysis to derive insight and support better business decisions.
Key Accountabilities- Conducts data analysis to make business recommendations (e.g., cost-benefit, invest-divest, forecasting, predictive, what-if, impact analysis, etc.)
- Owns data cleansing and accuracy for various data elements used publicly.
- Develops and manages processes, roles, security access, standards, data quality/integrity, etc. to ensure effective and efficient use of data throughout the enterprise.
- Ensures business process consistency and integration with other functional domains in order to meet DTE business requirements and solutions.
- Delivers effective presentations of findings and recommendations to multiple levels of stakeholders, creates visual displays of quantitative information.
- Develops, modifies, and automates reports, iteratively builds and prototypes dashboards to provide insights at scale, solving for analytical needs.
- Collaborates with cross‑functional stakeholders to understand their business needs, formulates complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables, and presentations, through scorecards and dashboards.
- Trains and enables self‑service reporting capability and use of business intelligence tools for their supported business unit(s).
- Develops actionable insights from in-depth data analysis to help DTE Energy focus on key decisions to improve products, services, and customer satisfaction.
- Minimum:
Bachelor's degree. - Individuals who will be obtaining their degree within nine months from submitting interest will be considered; however, verification of the degree will be required prior to starting in the job.
- Bachelor's or Master's degree with emphasis on coursework of a quantitative nature:
Computer Science, Data Sciences and Business - Background or coursework in in-depth quantitative analytics
- Experience in scripting with SQL, extracting large sets of data, and design of ETL flows
- Work experience in an interdisciplinary/cross‑functional field
- Utility or customer‑oriented industry experience
- PowerBI and Power Apps experience
- Intermediate-level experience with statistical packages (e.g, R, SAS, SPSS, Stata, MATLAB, etc)
- Experience articulating product questions, pulling data from relational databases technologies (e.g SAP, People Soft, ORACLE, SQL), using statistical tools to solve business problems, and to conduct indepth analysis to support…
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