Reliability Data Scientist Jobs (NOW HIRING)

We made history and now we work to transform the future - for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.

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.

Required Qualifications

• 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

• Programming: 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: A methodical approach to problem-solving and a high degree of attention to detail regarding data integrity.
• Cross-functional Collaboration: Ability to bridge the gap between data science and traditional hardware engineering.

• Communication: Capable of translating complex mathematical findings into business relevant strategies 

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 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.

This position is leadership level 6 and ranges from $115,500-$218,100.     
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
For more information on salary and benefits, click here: https://fordcareers.co/LL6

Visa sponsorship is not available for this position.

Domestic relocation is 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.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week. 

#LI-Hybrid

#LI-PW1

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