Reliability Data Scientist

Ford Motor • Dearborn, MI

3d • 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! At Ford, Reliability is at the core of everything we do. The Reliability Data Scientist is a specialized role that sits at the intersection of engineering, statistics, and machine learning. In this position, you will leverage large-scale datasets—including telematics, warranty claims, manufacturing logs, and sensor data—to predict product life cycles, identify failure modes, and drive proactive engineering improvements. Your goal is to transform data into actionable insights that improve product quality, reduce warranty costs, and enhance the customer experience.

Requirements

• Master’s Degree in Data Science, Statistics, Reliability Engineering, Systems Engineering, or a related quantitative field.
• 5+ years of experience in a data science role, preferably within manufacturing, automotive, aerospace, or energy sectors.
• Deep understanding of probability distributions (Normal, Lognormal, Exponential, and Weibull) and their applications in reliability.
• Understanding Ford customers and their desire for dependability, uptime and low total cost of ownership.
• Proficiency in Python (Pandas, NumPy, Scikit-learn, PyMC3/Stan) or R (survival, flexsurv).
• Advanced SQL skills for querying large relational databases.
• Familiarity with industry-standard software such as ReliaSoft (Weibull++, BlockSim) or JMP.
• Strong grasp of calculus-based statistics, specifically regarding hazard and reliability functions.
• Experience with Tableau, Power BI, or Matplotlib/Seaborn for communicating complex statistical trends to non-technical stakeholders.
• Knowledge of Physics of Failure (PoF) and how it integrates with empirical data models.
• A methodical approach to problem-solving and a high degree of attention to detail regarding data integrity.
• Ability to bridge the gap between data science and traditional hardware engineering.
• Capable of translating complex mathematical findings into business relevant strategies.

Nice To Haves

• Experience with Big Data tools (Spark, Hadoop, or Snowflake) is highly preferred.

Responsibilities

• Develop and deploy statistical models to predict component and system failures. This includes utilizing survival analysis, degradation modeling, and accelerated life testing (ALT) data.
• Apply advanced statistical methods to analyze censored data. You will frequently perform Weibull analysis and scale analysis to large data sets.
• Partner with Reliability and Quality Engineering teams to identify the "why" behind failures using anomaly detection and correlation analysis on fleet-wide data.
• Build pipelines to process high-frequency sensor data from the field to monitor real-time "health scores" for complex systems.
• Provide data-driven recommendations to design teams during the development phase to ensure new products meet or exceed reliability targets.
• Design and maintain dashboards that track Key Performance Indicators (KPIs) such as Mean Time Between Failures, Mean Time To Failure, and Repairs per Thousand.
• Use Monte Carlo simulations to estimate system-level reliability based on individual component performance and redundancy configurations.

Benefits

• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up childcare 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: Senior