- AI/ML & Generative AI: Architecting, developing, and deploying data leveraged through LLM models and toolsets such as Gemini Enterprise to build advanced generative AI solutions.
- Data Engineering & IIoT Pipelines: Designing factory data standards streamed through Kafka and MQTT for IoT telemetry.
- Data Anchoring & Strategy: Acting as the technical lead for data initiatives, defining data architecture standards, mentoring team members, and ensuring alignment with enterprise data strategies across hybrid environments.
- Cloud & Big Data Infrastructure: Designing and maintaining robust data architectures with traditional SQL, BigQuery for enterprise data warehousing, MongoDB for flexible NoSQL document storage, and Hadoop ecosystems for distributed big data processing.
- Data Modernization: Leading the migration and integration path from legacy on-premise systems (including legacy Hadoop clusters) to modern, cloud-native data platforms on GCP.
- Domain Expertise: Gaining a deep understanding of the core functionality of Industrial Systems to drive data-driven optimizations and predictive modeling.
- Model & Data Monitoring: Identifying and implementing monitoring solutions for data drift, model performance, and pipeline health using tools like Dynatrace, Splunk, and native cloud monitoring.
- Education: Master’s degree in Data Science, Computer Science, Computer Engineering, Statistics, or a related highly quantitative field.
- Experience: 5+ years of combined experience in Data Science, Data Engineering, and deploying AI/ML models into production environments.
- Technical Skills:
- Strong proficiency in programming languages for data and ML, specifically Python and SQL.
- Deep expertise in big data processing frameworks (e.g., Hadoop, Apache Spark, Kafka).
- Hands-on experience with streaming data and Industrial IoT protocols, specifically MQTT.
- Advanced database experience across relational and non-relational systems, including deep knowledge of BigQuery.
- Expertise in cloud platforms (GCP preferred) and leveraging advanced AI services like Gemini Enterprise and Vertex AI.
- Exposure to machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and predictive modeling techniques.
- Experience exposing ML models via RESTful APIs or microservices.
- Soft Skills:
- Proven ability to act as a "Data Anchor," guiding technical architecture and mentoring junior data scientists/engineers.
- Excellent communication, interpersonal, and presentation skills, with the ability to translate complex concepts to non-technical business stakeholders.
- Comfortable interacting with global plant IT and business customers to clarify needs and define data requirements.
- A quick learner, adaptable to changing environments, and highly effective within a diverse global team.
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.
Skills Required
- Master's degree in Data Science, Computer Science, Computer Engineering, Statistics, or related quantitative field.
- 5+ years combined experience in Data Science, Data Engineering, and deploying AI/ML models to production.
- Proficiency in Python.
- Proficiency in SQL.
- Experience with Hadoop and Hadoop ecosystems.
- Experience with Apache Spark.
- Experience with Kafka (streaming data).
- Hands-on experience with MQTT and Industrial IoT protocols.
- Advanced experience with BigQuery.
- Experience with MongoDB or other NoSQL document stores.
- Expertise in cloud platforms; GCP preferred.
- Experience with Gemini Enterprise and Vertex AI (advanced AI services).
- Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn.
- Experience exposing ML models via RESTful APIs or microservices.
- Experience with model and data monitoring tools (e.g., Dynatrace, Splunk) and pipeline health monitoring.
- Ability to act as a technical lead/data anchor and mentor junior data scientists/engineers.
- Strong communication and stakeholder-facing presentation skills.
Ford Motor Company Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Ford Motor Company and has not been reviewed or approved by Ford Motor Company.
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Pay Growth & Progression — The 2023 UAW–Ford agreement delivered immediate raises, restored cost-of-living adjustments, and accelerated progression to top rates for many hourly roles. These changes improved earnings trajectories compared with pre-2023 levels.
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Healthcare Strength — Hourly employees retained very low employee cost-sharing under the 2023–2028 UAW–Ford agreement, and salaried materials describe comprehensive day‑one medical, dental, and prescription coverage. Mental-health support and family‑building benefits add depth to the overall health package.
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Retirement Support — U.S. salaried roles feature a notable 401(k) contribution and match structure, and post‑2023 updates increased retirement contributions for many UAW‑represented employees. Together these elements strengthen long‑term financial security.
Ford Motor Company Insights
What We Do
Ford is a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation, we have sought to make the world a better place – one that benefits lives, communities and the planet. We are here to provide the means for every person to move and pursue their dreams, serving as a bridge between personal freedom and the future of mobility. In that pursuit, our 186,000 employees around the world help to set the pace of innovation every day.








