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 an exciting opportunity for you to join our expanding area of Telemetry and Observability.
Are you enthusiastic to mine raw data and realize its hidden value by architecting and building amazing, connected data solutions that benefit our customers? Would you love to accelerate our efforts in implementing advanced agentic solutions and ML model in production?
The Senior Data Scientist role resides within the Ford's Electric Vehicle organization. In this role, you will work on building scalable and robust data pipelines to process large volumes of manufacturing, repair, software update, call center case, and connected vehicle data to support the Ford telemetry and observability initiatives.
Collaborate across teams and internal organizations to develop a wider data architecture plan for all of Connected Vehicle Software.
Work with data stewards and data owners to source and understand data to ensure the best data transformation practices and processes.
Collaborate with data analytics stakeholders to streamline the data acquisition, processing, and presentation process.
Provide analysis of connected vehicle data to support new product developments and production vehicle improvements.
Contribute to the design and building of a Semantic Data layer to serve AI agents.
Work with ML Ops to design and implement robust, scalable data science and Machine Learning Operations (MLOps) pipelines primarily within cloud environments like Google Cloud Platform (GCP) and Amazon Web Services (AWS), ensuring efficient deployment and maintenance of AI solutions.
Lead the integration of new cloud technologies and AI tools (e.g., Vertex AI) into our workflows, continuously evaluating their potential and articulating their business value to drive innovation and efficiency.
Acquire a deep understanding of vehicle engineering problems, translating them into appropriate mathematical representations and AI/ML solutions (classification, prediction, intelligent automation).
Develop and maintain a data quality system, ensuring the overall quality and integrity of data and solutions throughout the development lifecycle, from data collection and cleaning to model deployment.
Build data pipelines to monitoring quality of data and performance of analytical models and agentic solutions.
Stay current on the latest practices in AI Agentic Solutions.
Work cross-functionally and have excellent technical interpretation skills to translate technical work to a variety of stakeholders.
Mentor more junior members of a data engineering team.
You will have...
Master's degree or foreign equivalent degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field, and 4 years of experience OR equivalent combination of education and experience (6+ years with Bachelor's Degree).
4 years of professional experience in:
Data engineering, data product development and software product launches
At least three of the following languages: Java, Python, Spark, Scala, SQL
3 years of cloud data/software engineering experience building scalable, reliable, and cost-effective production batch and streaming data pipelines using:
Data warehouses like Amazon Redshift, Microsoft Azure Synapse Analytics, Google BigQuery.
Workflow orchestration tools like Airflow.
Relational Database Management System like MySQL, PostgreSQL, and SQL Server.
Real-Time data streaming platform like Apache Kafka, GCP Pub/Sub
Microservices architecture to deliver large-scale real-time data processing application.
REST APIs for compute, storage, operations, and security.
DevOps tools such as Tekton, GitHub Actions, Git, GitHub, Terraform, Docker.
Project management tools like Atlassian JIRA.
Comfort working in ambiguous environments where problems are not always well-defined, and solutions require innovative thinking
Even better if you have...
Ph.D. or foreign equivalent degree in Computer Science, Software Engineering, Information System, Data Engineering, or a related field.
2 years of experience with ML Model Development and/or MLOps.
Committed code to improve open-source data/software engineering projects
Experience architecting cloud infrastructure and handling application migrations/upgrades.
GCP Professional Certifications.
Demonstrated passion to mine raw data and realize its hidden value.
Passion to experiment/implement state of the art data engineering methods/techniques.
Experience working in an implementation team from concept to operations, providing deep technical subject matter expertise for successful deployment.
Experience implementing methods for automation of all parts of the pipeline to minimize labor in development and production.
Analytics skills to profile data, troubleshoot data pipeline/product issues.
Ability to simplify, clearly communicate complex data/software ideas/problems and work with cross-functional teams and all levels of management independently.
Ability to mentor and advise junior team members
Develop exceptional analytical data products using both streaming and batch ingestion patterns on Google Cloud Platform with solid data warehouse principles.
Build data pipelines to monitoring quality of data and performance of analytical models and agentic solutions.
Maintain the infrastructure of the data platform using terraform and continuously develop, evaluate, and deliver code using CI/CD.
Collaborate with data analytics stakeholders to streamline the data acquisition, processing, and presentation process.
Implement an enterprise data governance model and actively promote the concept of data - protection, sharing, reuse, quality, and standards.
Enhance and maintain the DevOps capabilities of the data platform.
Continuously optimize and enhance existing data solutions (pipelines, products, infrastructure) for best performance, high security, low vulnerability, low costs, and high reliability.
Work in an agile product team to deliver code frequently using Test Driven Development (TDD), continuous integration and continuous deployment (CI/CD).
Promptly address code quality issues using SonarQube, Checkmarx, Fossa, and Cycode throughout the development lifecycle.
Perform any necessary data mapping, data lineage activities and document information flows.
Monitor the production pipelines and provide production support by addressing production issues as per SLAs.
Provide analysis of connected vehicle data to support new product developments and production vehicle improvements.
Provide visibility to data quality/vehicle/feature issues and work with the business owners to fix the issues.
Demonstrate technical knowledge and communication skills with the ability to advocate for well-designed solutions.
Continuously enhance your domain knowledge of connected vehicle data, connected services and algorithms/models/solutions developed by data scientists and AI engineers.
Stay current on the latest data engineering practices and contribute to the technical direction of the company while keeping a customer-centric approach.
Master's degree or foreign equivalent degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field, and 4 years of experience OR equivalent combination of education and experience (6+ years with Bachelor's Degree).
4 years of professional experience in:
Data engineering, data product development and software product launches
At least three of the following languages: Java, Python, Spark, Scala, SQL
3 years of cloud data/software engineering experience building scalable, reliable, and cost-effective production batch and streaming data pipelines using:
Data warehouses like Amazon Redshift, Microsoft Azure Synapse Analytics, Google BigQuery.
Workflow orchestration tools like Airflow, Cloud Run.
Relational Database Management System like MySQL, PostgreSQL, and SQL Server.
Real-Time data streaming platform like Apache Kafka, GCP Pub/Sub
Microservices architecture to deliver large-scale real-time data processing application.
REST APIs for compute, storage, operations, and security.
DevOps tools such as Tekton, GitHub Actions, Git, GitHub, Terraform, Docker.
Project management tools like Atlassian JIRA.
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 and ranges from $99,600-$146,600., This position is a salary grade 8 and ranges from $115,000-$162,900.
For more information on salary and benefits, click here:
Visa sponsorship is not 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.
This position is hybrid with a requirement to be onsite four or more days per week. #LI-Hybrid
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