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Applied Data ScientistFord Motor Company • United States
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Applied Data Scientist

Ford Motor Company
  • US
    United States
  • US
    United States
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About

In this position...
As an Applied Data Scientist within the Advanced Driver Assist Systems (ADAS) domain, you will leverage connected vehicle, diagnostic, and warranty data to (1) enhance ADAS feature performance and (2) predict, identify, and root-cause high warranty costs. In this dual role, you will architect complex data products and Machine Learning models as well as develop AI tools, such as RAG and Text-to-SQL Code Gen/Code Execution products. You will work directly with industry-leading ADAS technologies, including BlueCruise hands-free driving.
What you'll do...
Define and manage data collection requirements for the ADAS organization, addressing both field issues and the development of innovative new features.
Collaborate with Ford’s Connected Vehicle Data Enablement (CVDE) team to implement custom data collection strategies.
Analyze large-scale datasets in GCP using BigQuery (SQL) and Python.
Develop data products and Machine Learning models by fusing multi-domain sources, including CVDE data, warranty claims, customer verbatims, weather, and road/lane geometry.
Execute ML model inference and perform sensitivity analysis on data products to develop a deep understanding of the data.
Democratize insights across the organization through automated “Push Analytics.”
Build Text-to-SQL and code-generation/execution AI tools to enable “Custom Pull Analytics,” allowing Subject Matter Experts (SMEs) to retrieve bespoke insights.
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.
You'll have...
Education: Bachelor’s degree in data science, Computer Science, Statistics, Mathematics, or a related Engineering field.
Experience: Minimum 3+ years of professional experience in Data Science, Machine Learning, or Data Engineering.
Programming & Data: Proficiency in Python and advanced SQL for data manipulation and analysis.
Cloud Experience: 2+ years of hands-on experience working with large-scale datasets in a cloud environment (preferably GCP/BigQuery).
Machine Learning: Proven experience building, training, and running inference on Machine Learning models to solve real-world problems.
Data Engineering: Ability to perform "Data Fusion" by joining and cleaning disparate, multi-domain datasets.
Visualization: Experience creating data visualizations or dashboards using tools such as PowerBI, Looker Studio, or Superset.
Significant Exposure to AI tooling and eco system: 1+ years of experience with Generative AI technologies, specifically building RAG pipelines and Text-to-SQL or Code-Generation applications.
Communication: Strong ability to translate business requirements from Subject Matter Experts (SMEs) into technical data collection and analysis plans.
Even better, you may have...
Education: Master’s degree in Data Science, Artificial Intelligence, Computer Science, or a related quantitative field.
Experience: 5+ years of professional experience, with a track record of delivering end-to-end data products in a corporate or industrial setting.
Advanced AI: 2+ years of experience with Generative AI technologies, specifically building RAG pipelines and Text-to-SQL or Code-Generation applications.
Application Development: Experience building interactive data/AI apps using the Python ecosystem (e.g., Chainlit, Streamlit, or Dash).
Domain Expertise: Background in ADAS, vehicle telematics, diagnostics, or automotive warranty/quality data.
Geospatial Data: Experience working with environmental or spatial data sources such as road/lane geometry and weather data.
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:
• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time.
This position is a salary grade 7-8.
For more information on salary and benefits, click here: https://fordcareers.co/GSR (https://urldefense.com/v3/__https:/fordcareers.co/GSR__;!!N_LtwI-RPugbI9wg0dJn!GJBaQhGT8ImSM382k2yj0PnK1zsZVOvxYyslyK6-C-jgruT8nXl2aBgKvu4Se4iS88UFq0IRA5Ue9A6jGA$)
Visa sponsorship is available for this position.
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.
Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week. #LI-LB1
  • United States

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  • English
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