Expert 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. Testing Required: Not Applicable 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 SummaryActs as a technical expert and project leader for the most challenging data science projects. Provides highly technical and analytical assessments of business priorities to senior leadership and drives the implementation of analytic solutions. Acts as a strong influencer and change agent in the organization to advance a data–based decision-making culture. Oversees and coaches the team of data scientists to run analytical experiments methodically, evaluate alternative models, and develop predictive models to forecast business performance metrics. Communicates effectively with technical and non-technical stakeholders with strong domain expertise and business acumen. Leads the research and development of new technologies and best practices within the industry to recommend approaches and strategies that develop the organization’s analytical capabilities—Span of Control: 0, Individual Contributor.

Requirements

Bachelor’s degree and 10 years of experience, inclusive of 3 years of leading experience working as a team or project lead in a data analytical or computer programming function; or
Master’s degree and 8 years of experience, inclusive of 3 years of leading experience working as a team or project lead in a data analytical or computer programming function; or
Ph.D. degree and 6 years of experience, including 3 years of leading experience working as the team or project lead in a data analytical or computer programming function
5 years of experience in qualitative and quantitative analytics (e.g., data mining, regression analysis, hypothesis testing, A/B testing, predictive modeling, model optimization, time series analysis, cluster analysis, natural language processing/text analytics, and segmentation)
Intermediate-level competency using advanced Excel and statistical tools (e.g., Minitab, Alteryx, advanced Excel with VBA, R, Python, SAS, SPSS, Stata, MATLAB, etc.) to conduct in-depth analysis to support decision making
Proven expertise in articulating business questions and pulling data from relational databases (e.g., ORACLE, SQL SERVER)
Intermediate-to advanced-level programming skills in SQL, Python, R, and in visualization tools such as Power BI, Tableau
Intermediate- to advanced- level skills in data modeling, data structure, metadata, and the application of complex SQL queries with data from multiple sources, including a Big Data platform (e.g., Azure ADLS and Databricks)
Experience in designing, building, and supporting a production pipeline for data transformation and validation
Advanced skills of applied research design, machine learning, prediction, and optimization (e.g., multivariate statistical analysis, unsupervised and supervised learning, predictive modeling, Monte Carlo simulation)
Exceptional track record of successfully delivering large-scale analytical models and systems that result in substantial positive impact on business operations or customer satisfaction
Intermediate-level or higher Continuous Improvement knowledge, skills, and certifications
Self-starter and learning capability in advancing skillset in business processes, data science, and communications
Advanced interpersonal, analytical, and problem-solving skills, including the ability to communicate technical information and complex data analytics to a non-technical audience
Experience with leading large projects end-to-end with customer facing and system integration
Experience with mentoring and coaching data scientists
Experience with agile process development
Experience using version control (e.g., Git)

Nice To Haves

Master’s or Ph.D degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Econometrics, etc.)
Advanced business acumen and utility/energy industry experience
Deep interest and aptitude in data, metrics, analysis, trends, statistics, and program evaluation
Advanced project management skills
Experience with publications or conference presentations in a related subject

Responsibilities

Leads data science projects from end-to-end, collaborating with cross-functional stakeholders, identifying business requirements, gathering data, researching analytics solutions, and integrating solutions into business processes
Conducts advanced statistical analysis to determine trends and significant data relationships, and proactively recommends 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 (e.g., cost-benefit, invest-divest, forecasting, predictive, what-if, impact analysis, etc.)
Prepares and delivers insightful presentations and action recommendations. Educates leaders and crews on complex analytical findings in laymen terms and with storytelling/data visualization
Identifies and evaluates technologies and provides strategic inputs to advance the organization’s analytics capabilities
Mentors the team of data scientists by guiding their professional development in conjunction with the team manager
Actively researches new technologies in related subjects and supports the organization to develop data analytics strategies and roadmaps

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