Principal Supervisor - Data Science

DTE Energy•Detroit, MI

5d•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

Proficient in quantitative analytics (e.g., data mining, regression analysis, hypothesis testing, A/B testing, machine learning modeling, including multivariate statistical analysis, natural language processing, unsupervised and supervised learning, deep learning, predictive modeling, and model optimization in production).
Intermediate- to advanced-level knowledge and skills in data modeling, data structures, and the application of complex SQL queries with data from multiple sources, including a Big Data platform (e.g., Hadoop, AWS, Azure).
Proficient in programming skills such as SQL, C/C++/C#, Java, R, Python, PHP, or SAS.
Ability to develop models in a Big Data cloud environment and deploy models in production.
Intermediate-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 in articulating business questions, pulling data from relational databases (e.g., SAP Business Warehouse (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 determine the appropriate analytical approach to conduct in-depth analysis to support decision-making).
Adept with multiple business intelligence tools and platforms (e.g., SAP Business Objects, Microsoft Power BI, Microsoft Azure, AI, and machine learning tools).
Ability to lead analytical data projects across functional teams, including coaching and feedback of other team members on analytic approaches.
Excellent communication skills, including the ability to interact with and influence decision-making by non-analytical business audiences.
Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Information Systems, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational Psychology, and Econometrics, etc.) or Business Administration, and 7 years of experience working in a data analytical, computer programming, or engineering function, inclusive of two years of experience leading analytical projects; OR Master’s degree in a quantitative field (e.g., Statistics, Computer Science, Information Systems, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational Psychology, and Econometrics, etc.) or Business Administration, and 5 years of experience working in a data analytical, computer programming, or engineering function, inclusive of two years of experience leading analytical projects.

Nice To Haves

Experience in quantitative analysis, query design, data visualization, statistical analysis, and predictive analytics

Responsibilities

Leads team that develops analytics strategies, identifies effective performance metrics, and recommends Business Intelligence (BI) technologies and applications.
Provides oversight of analytical professionals in developing and implementing Business Intelligence (BI), Artificial Intelligence (AI), and Machine Learning (ML) projects.
Advises senior leadership and enterprise stakeholders using sound analyses and data-driven insights.
Oversees a team of analysts and data scientists in the application of data science methods to identify business opportunities, predict performance outcomes, and provide tactical and strategic recommendations.
Translates business and analytics strategies into multiple short-term and long-term projects, and ensures end-to-end execution of projects.
Supports scientific, measurable, and fact-driven approaches by adding statistical rigor to business recommendations.
Implements new, industry-leading statistical, mathematical, machine learning, or other methodologies for modeling or analyses.
Discovers insights from Big Data to help shape or meet specific business needs and goals.
Identifies and evaluates technologies and provides strategic input to advance the organization’s analytics capabilities.
Utilizes business expertise to translate goals into data-based deliverables, such as predictive models, pattern detection analysis, or optimization algorithms and methods.
Ensures the accomplishment of the following core supervisory/management functions for a given group(s) within a business unit: planning, organizing, directing the performance of ongoing activities and/or special/ad hoc assignments, staffing (employee selections, training, coaching and performance management, time entry), coordinating, reporting, and budgeting.
Leads the continuous improvement commitment and efforts for the team, including designing processes, establishing quality and quantity standards and metrics, collecting, refining, adapting, and communicating best practices, sharing knowledge, and systematically developing staff; uses process design outcomes to solve problems.