Product Manager & Data Science Supervisor

Product Manager & Data Science Supervisor

Dearborn, MI, United States (Hybrid)

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow’s transportation.

Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics, and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.

What you'll be able to do:

Product Manager & Data Science Supervisor - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a hybrid position whereby the employee will work both from home and from the aforementioned worksite. Hence, the employee must live within a reasonable commuting distance from the worksite. Supervise a global cross-functional team composed of data scientists, data analysts, data engineers, product designers, program managers, and software engineers.

Provide leadership, mentorship, and guidance to ensure effective collaboration and successful delivery of analytics-driven solutions and product initiatives. Foster an environment of open communication and teamwork, facilitating alignment across diverse technical and business disciplines to achieve organizational goals and continuous improvement. Work closely with stakeholders throughout Ford Operations/Enterprise to identify opportunities to improve process optimization and efficiency via data-driven approaches.

Lead, coordinate, and communicate work across multiple teams. Organize large datasets and get actionable insights for business. Apply data mining, data transformation, and develop statistical, optimization, and machine learning models. Create meaningful data visualization, outputs files and presentations to communicate findings with stakeholders. Work with IT to implement analytics tools into a production environment. Develop analytic models using skills such as data wrangling, algorithm design, prototype and deployment.

Support cross-function teams on Reductive Design decisions with insights gained from analytics tools and visualization from the data. Problem formulation for Reductive Design problems. Acquire a deep understanding of business problems, define the problem scope from business requests and translate business requirements to analytical projects through Design Thinking. Work effectively with a wide range of stakeholders and functional teams. Interpret results and communicate them to technical and non-technical audiences, cross functional teams, and executive leadership.

Support ad hoc requests and serve as insight provider/consultant for business units. Have ownership of the project, create a project plan, track project progress, and host user group meetings. Run efficient SQL to process TB-level datasets. Design a visual interface for users to interact with the data, or persuading visualization. Provide training and maintenance of implemented tools to stakeholders. Build advanced analytics models in the supply chain space.

You'll have…

Master’s degree or foreign equivalent in Data Science, Mathematics, Applied Statistics, Computer Science, Mechanical Engineering, Operations Research or a related field and 3 years of experience in the job offered or a related occupation. 3 years of experience with each of the following skills is required:
1. Programming languages, Python or R, and SQL for complex data transformation and analysis.
2. Applying machine learning, statistical modeling, and deep learning techniques to solve business problems and inform product development.
3. Leveraging cloud platforms and big data technologies for…