Applied Data Scientist: Vehicle Prognostics & Edge ML

Ford; Dearborn (MI); Hybrid; USD 85,400 - 160,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Vehicle discount program

Tuition assistance

Paid holidays

Job summary

Ford is seeking an Applied Data Scientist for its EVDD team in a hybrid role. You will lead prognostic feature development from concept to vehicle deployment, fusing physics with machine learning to predict degradation and estimate remaining useful life across EV and ICE powertrains.

You will translate models into optimized C++ for on-board ECUs, build high-frequency DSP pipelines, and deploy robust diagnostics using big data tools.

Qualifications

• Bachelor's degree in a relevant field or equivalent experience.
• 4+ years applying statistical methods (ANOVA, PCA, causal inference, etc.).
• 3+ years Python and SQL experience.
• Experience with embedded controls and physics-based modeling.
• Experience with DSP data structures and time-series analysis.
• Strong self-motivation, analytical and communication skills.

Responsibilities

• Own the prognostic feature development lifecycle from concept to production.
• Pioneer Physics-Informed Machine Learning for hybrid prognostic models.
• Architect prognostics and RUL frameworks for subsystems.
• Deploy edge models in C++ on ECUs.
• Build high-frequency DSP pipelines and time-series analytics.
• Design multi-sensor fault detection and isolation (FDI).
• Apply statistical causal inference to identify root causes.
• Manage end-to-end pipeline from MATLAB/Simulink to production.
• Synthesize deep domain knowledge into diagnostics.
• Handle big data calibration using Python, SQL, Spark, Hadoop.
• Collaborate cross-functionally to ensure production code integration.

Skills

Python

SQL

C++

DSP

Time-series

Statistics

MATLAB/Simulink

Embedded controls

Education

Bachelor's degree in mechanical/electrical/computer science/engineering/physics/math

Tools

MATLAB

Simulink

ETAS

ATI

Spark

Hadoop

R

C++ toolchains

Job description

Ford is seeking an Applied Data Scientist for its EVDD team in a hybrid role. You will lead prognostic feature development from concept to vehicle deployment, fusing physics with machine learning to predict degradation and estimate remaining useful life across EV and ICE powertrains.

You will translate models into optimized C++ for on-board ECUs, build high-frequency DSP pipelines, and deploy robust diagnostics using big data tools.