Applied Data Scientist

Ford Ford · Auto · Dearborn, MI +1 · Research and Advance Engineering

Applied Data Scientist role focused on enhancing ADAS feature performance and predicting warranty costs by leveraging connected vehicle data. The role involves architecting data products and ML models, developing AI tools like RAG and Text-to-SQL, and building interactive AI/ML applications. Requires strong Python, SQL, cloud (GCP/BigQuery), and ML model experience, with a specific emphasis on Generative AI technologies.

What you'd actually do

  1. Define and manage data collection requirements for the ADAS organization, addressing both field issues and the development of innovative new features.
  2. Collaborate with Ford’s Connected Vehicle Data Enablement (CVDE) team to implement custom data collection strategies.
  3. Develop data products and Machine Learning models by fusing multi-domain sources, including CVDE data, warranty claims, customer verbatims, weather, and road/lane geometry.
  4. Build Text-to-SQL and code-generation/execution AI tools to enable “Custom Pull Analytics,” allowing Subject Matter Experts (SMEs) to retrieve bespoke insights.
  5. Develop interactive AI/ML applications using the Python ecosystem (e.g., Chainlit, Dash, or Streamlit) and design dashboards in Superset, PowerBI, or Looker Studio for standardized reporting.

Skills

Required

  • Python
  • SQL
  • GCP/BigQuery
  • Machine Learning models
  • Data Fusion
  • Generative AI technologies
  • RAG pipelines
  • Text-to-SQL
  • Code-Generation applications

Nice to have

  • Master’s degree in Data Science, Artificial Intelligence, Computer Science, or a related quantitative field
  • 5+ years of professional experience
  • 2+ years of experience with Generative AI technologies
  • Interactive data/AI apps development
  • ADAS domain expertise
  • vehicle telematics
  • diagnostics
  • automotive warranty/quality data
  • Geospatial Data
  • road/lane geometry
  • weather data

What the JD emphasized

  • building RAG pipelines
  • Text-to-SQL
  • Code Gen/Code Execution
  • Generative AI technologies

Other signals

  • building RAG pipelines
  • Text-to-SQL Code Gen/Code Execution products
  • AI/ML applications
  • democratize insights
  • custom data collection strategies