Vehicle Connected Data Manager

Ford Motor • Dearborn, MI

4d • Hybrid

About The Position

This role serves as an enterprise early warning leader, transforming large-scale connected vehicle telemetry into actionable insights that identify emerging quality issues before customer impact occurs. The position combines data science, automotive systems expertise, and cross-functional leadership to drive predictive quality detection, accelerate root cause identification, and improve enterprise quality metrics. The ideal candidate brings deep experience in automotive systems, big data analytics, AI/ML-driven detection methods, and technical leadership within fast-paced product development and launch environments.

Requirements

• Master’s degree in Data Science, Computer Science, Electrical Engineering, Statistics, Mathematics, or related technical field.
• 6+ years of experience in automotive engineering, connected vehicle analytics, data science, or quality analytics.
• 3+ years of experience leading cross-functional technical initiatives with measurable business outcomes.
• Strong experience with big data analytics platforms and cloud ecosystems including GCP, BigQuery, AWS, or Azure.
• Proven experience developing scalable analytics solutions using large telemetry or sensor-based datasets.
• Hands-on experience with anomaly detection, predictive analytics, statistical modeling, or machine learning applications.
• Deep understanding of vehicle diagnostics, CAN/Ethernet communication architectures, and DTC strategies.
• Strong technical familiarity across automotive functional domains including Powertrain, Electrified Powertrain, ADAS, Infotainment, Body Controls, Thermal Systems, and Vehicle Networking.
• Experience building automated data pipelines and operational analytics solutions supporting business-critical functions.
• Exceptional analytical, problem-solving, and cross-functional leadership capabilities.
• Strong executive communication and technical storytelling skills.

Nice To Haves

• Experience operating within vehicle launch, quality, or product development environments preferred.
• Programming experience in Python and embedded or systems-level scripting environments such as Lua.
• MBA or management-focused graduate education is a plus.
• Strong understanding of Ford Connected Data practices – data engineering pipelines, data privacy standards, customer consent regulations.
• Experience with AI/ML model deployment and operationalization.
• Familiarity with connected vehicle telemetry architectures and cloud ingestion frameworks.
• Experience developing visualization tools and executive analytics dashboards.
• Knowledge of structured root cause methodologies such as 8D or 5-Why.
• Experience supporting software-defined vehicle and over-the-air (OTA) ecosystems.

Responsibilities

• Develop and deploy advanced analytics frameworks to identify anomalous vehicle behaviors, diagnostic trends, and emerging quality risks across millions of connected vehicles.
• Apply statistical methods, machine learning, and AI-driven detection techniques to improve early warning capabilities and reduce time-to-detection for vehicle quality issues.
• Design scalable algorithms and data models capable of analyzing billions of telemetry and diagnostic data points across vehicle platforms.
• Lead enterprise use of connected vehicle data throughout the product lifecycle, including pre-production validation, launch monitoring, and in-market quality surveillance.
• Define strategies for leveraging cloud-based telemetry, diagnostic, and software interaction data to improve product quality outcomes.
• Drive continuous improvement of detection logic, escalation frameworks, and data-driven quality processes.
• Lead use of connected data for quality across the entire product lifecycle, from TT builds in CVLQ to MP1 builds in EWRT and post-OKTB data in UCS.
• Lead deep-dive investigations into software, hardware, calibration, and systems integration issues using connected vehicle data.
• Correlate signals across vehicle functional domains to identify root causes and systemic quality trends.
• Partner with Product Development, Software, Hardware, Manufacturing, and Quality teams to drive issue resolution and containment actions.
• Drive development of automated analytics pipelines, AI-enabled monitoring tools, and executive dashboards supporting enterprise quality initiatives.
• Partner with data engineering and platform teams to improve data accessibility, reliability, and scalability across cloud environments.
• Champion modern data science methodologies and operational analytics best practices within the organization.
• Lead cross-functional initiatives focused on launch quality improvement, issue prevention, and reduction of customer-impacting failures.
• Translate highly technical findings into concise executive-level insights and strategic recommendations.
• Influence decision-making across engineering, quality, and leadership organizations without direct authority.

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: Manager