Reliability Data Scientist

Ford Motor Company

Specialized Reliability Data Scientist role at Ford focusing on engineering, statistics, and machine learning. Leveraging large datasets to improve product quality and enhance customer experience.

Posted 5/5/2026full-timeDearborn • Missouri • 🇺🇸 United StatesMid-LevelSenior💰 $115,500 - $218,100 per yearWebsite

Tech Stack

Tools & technologies

HadoopNumpyPandasPythonScikit-LearnSparkSQLTableau

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

Education: Master’s Degree in Data Science, Statistics, Reliability Engineering, Systems Engineering, or a related quantitative field.
Experience: 5+ years of experience in a data science role, preferably within manufacturing, automotive, aerospace, or energy sectors.
Statistical Expertise: Deep understanding of probability distributions (Normal, Lognormal, Exponential, and Weibull) and their applications in reliability.
Customer Focus: Understanding Ford customers and their desire for dependability, uptime and low total cost of ownership.
Technical Skills: Proficiency in Python (Pandas, NumPy, Scikit-learn, PyMC3/Stan) or R (survival, flexsurv).
Data Management: Advanced SQL skills for querying large relational databases. Experience with Big Data tools (Spark, Hadoop, or Snowflake) is highly preferred.
Reliability Tools: Familiarity with industry-standard software such as ReliaSoft (Weibull++, BlockSim) or JMP.
Mathematics: Strong grasp of calculus-based statistics, specifically regarding hazard and reliability functions
Visualization: Experience with Tableau, Power BI, or Matplotlib/Seaborn for communicating complex statistical trends to non-technical stakeholders.
Physics of Failure: Knowledge of Physics of Failure (PoF) and how it integrates with empirical data models.
Soft Skills & Competencies: Analytical Rigor, Cross-functional Collaboration, Communication skills.

Benefits

Comp & perks

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.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

statistical modelssurvival analysisdegradation modelingaccelerated life testingWeibull analysiscorrelation analysisMonte Carlo simulationsPythonSQLcalculus-based statistics

Soft Skills

analytical rigorcross-functional collaborationcommunication skillscustomer focus