Product Manager & Data Science Supervisor

Ford Ford · Auto · Dearborn, MI +1 · Global Data Insight & Analytics

This role supervises a global cross-functional team of data scientists, analysts, engineers, and designers to deliver analytics-driven solutions and product initiatives. The responsibilities include identifying opportunities for process optimization via data-driven approaches, organizing large datasets, applying data mining and machine learning models, creating visualizations, and working with IT to implement analytics tools. The role involves developing analytic models, supporting Reductive Design decisions, formulating problems, translating business requirements into analytical projects, and communicating findings to various stakeholders. It also includes project ownership, planning, tracking, and building advanced analytics models in the supply chain space, with a specific requirement for developing, fine-tuning, and deploying LLMs for NLP tasks.

What you'd actually do

  1. Supervise a global cross-functional team composed of data scientists, data analysts, data engineers, product designers, program managers, and software engineers.
  2. Provide leadership, mentorship, and guidance to ensure effective collaboration and successful delivery of analytics-driven solutions and product initiatives.
  3. Work closely with stakeholders throughout Ford Operations/Enterprise to identify opportunities to improve process optimization and efficiency via data-driven approaches.
  4. Apply data mining, data transformation, and develop statistical, optimization, and machine learning models.
  5. Build advanced analytics models in the supply chain space.

Skills

Required

  • Python or R
  • SQL
  • Machine learning
  • Statistical modeling
  • Deep learning techniques
  • Cloud platforms
  • Big data technologies
  • Large language models (LLMs)
  • NLP tasks
  • Text classification
  • Summarization
  • Conversational AI
  • Communication of technical findings
  • Project management
  • Agile environments
  • UX principles
  • Software development lifecycle
  • Version control tools
  • Product management tools (Jira, Confluence, or Figma)
  • Product requirements definition
  • Roadmap development
  • Product documentation
  • User stories

Nice to have

  • Data wrangling
  • Algorithm design
  • Prototype and deployment
  • Reductive Design
  • Design Thinking
  • Data visualization
  • Supply chain analytics

What the JD emphasized

  • 3 years of experience with each of the following skills is required:
  • Programming languages, Python or R, and SQL for complex data transformation and analysis.
  • Applying machine learning, statistical modeling, and deep learning techniques to solve business problems and inform product development.
  • Leveraging cloud platforms and big data technologies for scalable data solutions.
  • Developing, fine-tuning, and deploying large language models (LLMs) for NLP tasks, including text classification, summarization, and conversational AI.
  • Communicate complex technical findings and business impacts to diverse technical and non-technical stakeholders.
  • Managing project timelines, scope, and resource allocation within Agile environments.
  • Defining and executing product requirements and roadmaps, including the creation of product documentation and user stories.

Other signals

  • Develop analytic models using skills such as data wrangling, algorithm design, prototype and deployment.
  • Build advanced analytics models in the supply chain space.
  • Developing, fine-tuning, and deploying large language models (LLMs) for NLP tasks, including text classification, summarization, and conversational AI.