Senior Data Scientist

DTE Energy•Detroit, MI

2d•Hybrid

About The Position

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.

Requirements

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
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

Nice To Haves

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

Responsibilities

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