Connected Vehicle Data Engineer

Ford • Dearborn, MI

18h • $65,100 - $166,200 • Hybrid

About The Position

Product Development uses design thinking & user experience methods to deliver breakthrough products and services that delight our customers. We bring innovative, exciting, and sustainable ideas to life. We have opportunities around the world for you to contribute to advancements in autonomy, electrification, smart mobility technologies, and more!

Requirements

• Bachelor’s Degree in Engineering, Data Science, Computer Science, Statistics, or a related quantitative field.
• 3+ years of analytical, querying, and programming experience (SQL, Python, PySpark/Spark, and similar big data tools).
• 2+ years of experience in the automotive industry (Product Development, Calibration, and/or Quality).
• Proven experience building and applying Machine Learning models (such as supervised/unsupervised learning, regression, classification, or anomaly detection) to solve physical systems or engineering problems.

Nice To Haves

• Master’s Degree or Ph.D. in Engineering, Data Science, Statistics, Machine Learning, or a similar quantitative field.
• 5+ years of propulsion systems experience with a strong understanding of delivering calibration processes.
• 2+ years of experience in the Connectivity eco-system, delivering big data analytics projects from concept to production.
• Strong knowledge of statistical inference, risk quantification methods, and reliability engineering.
• Experience with Agile methodologies, Git version control, and CI/CD pipelines for ML models (MLOps).
• Ability to write sophisticated, optimized SQL queries to extract and transform massive, unstructured CV datasets.
• Ability to take complex, ambiguous engineering problems and break them down to build, prioritize, and implement actionable data science solutions.
• Exceptional communication and visualization skills, with the ability to build intuitive dashboards (e.g., Looker, PowerBI) to enable inference and decision-making by customers and stakeholders.
• Strong team player with proven experience and a willingness to take ownership of a topic and successfully bring it to completion.
• Google Cloud Platform (GCP) or Professional Data Engineer/Machine Learning Engineer Certification.

Responsibilities

• Apply Machine Learning to Powertrain Data: Develop, train, and deploy machine learning models on curated powertrain data to detect anomalies, identify early-warning quality indicators, and predict component degradation.
• Quantify & Assess Risk: Use statistical modeling and ML inference to quantify, assess, and prioritize risks associated with powertrain field quality issues, enabling data-driven decision-making.
• Perform Inferential Analytics: Conduct inferential and diagnostic analytics to identify root causes of complex engineering and quality problems, translating CV big data into actionable insights.
• Establish Stakeholder Alignment: Build strong working relationships with key stakeholders in Product Development to ensure that plans and requirements are fully understood, and issues are resolved effectively and efficiently.
• Debug & Resolve Issues: Debug, root-cause, and resolve propulsion systems quality issues with cross-functional teams, leveraging connected vehicle data, ML models, and enterprise toolsets.
• Foster Data Collection: Drive and optimize connected vehicle data collection strategies for solving engineering problems and characterizing customer usage patterns.
• Query & Manipulate Big Data: Write highly proficient BigQuery SQL (and similar language) queries to extract, clean, and interpret massive, connected vehicle datasets in the propulsion systems domain.
• Develop Data Pipelines: Design, build, and own robust data pipelines and workflows using Python, PySpark, and modern data engineering tools to support ML model training and deployment.
• Coordinate Data Creation: Partner with vehicle software teams to define and create new connected vehicle data elements, and support the validation of these new telemetry signals.
• Validate via Calibration Tools: Utilize in-vehicle calibration tools (ATI / ETAS) to collect high-frequency data to validate connected data and verify ML model predictions on key propulsion features and subsystems.
• Synthesize & Communicate Insights: Summarize and present complex machine learning models, statistical analyses, and big data findings in a simplified, visual fashion to both technical and non-technical audiences, including executive leadership.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level