# Vehicle Prognostics - Applied Data Scientist

**Company**: Ford Motor Company
**Location**: Dearborn, MI
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $85,400-$160,000
**Category**: IT
**Industry**: Automotive
**Wikidata**: https://www.wikidata.org/wiki/Q44294

**Apply**: https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/65931?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_8c9c886c-24b

## Description

Ford's Electric Vehicles, Digital and Design (EVDD) team is seeking an Applied Data Scientist to work on Vehicle Prognostics. The team is responsible for delivering the company's vision of a fully electric transportation future. As an Applied Data Scientist, you will develop and deliver breakthrough Prognostic Features to study and predict the degradation or occurrence of a problem in a vehicle component/system.

Responsibilities:

- Own the process for prognostic feature development from conceptual to feature deployment to production vehicles.

- Pioneer Physics-Informed Machine Learning (PIML) to develop hybrid, high-fidelity prognostic models.

- Architect Prognostics & RUL Frameworks to accurately estimate the Remaining Useful Life (RUL) of critical vehicle subsystems.

- Deploy Edge Models in C++ to bridge the gap between cloud-based data science and resource-constrained on-board vehicle electronic control units (ECUs).

- Harness High-Frequency Signal Processing to extract clean, high-frequency physical signatures from multi-sensor vehicle networks.

- Design Multi-Sensor Fault Detection & Isolation (FDI) frameworks capable of real-time Fault Detection and Isolation (FDI).

- Apply Statistical Causal Inference to differentiate between mere correlation and true physical root causes of component degradation.

- Own the End-to-End Pipeline (HIL to Production) and direct the entire prognostic lifecycle.

- Synthesize Deep Subsystem Domain Knowledge and partner with EV and ICE component subject matter experts.

- Build Scale with Big Data & Calibration Tools and ingest large-scale telemetry data using Python, SQL, Spark, and Hadoop.

Qualifications:

- Bachelor's in Mechanical, Electrical, Computer Science, Computer Engineering, Physics, Mathematics or related fields.

- 4+ years of experience in practicing statistical methods and their accurate application.

- 3+ years of experience with Python, SQL, and related modules.

- Experience with embedded controls, onboard Diagnostic, Sensor Processing, General First Principles Physics Modeling and simulation using numerical computational tools.

- Self-motivated, strong analytical, excellent interpersonal and communication skills required.

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.

## Skills

### Required
- Python
- SQL
- Machine Learning
- Data Science
- C++
- MATLAB
- Simulink
- Digital Signal Processing
- Statistical Analysis

### Nice to have
- Physics-Informed Machine Learning
- Prognostics and Health Management
- Dynamic Systems
- Control
- Robotics
- Spark
- Hadoop
- R
- ATI
- ETAS

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Source: [Apply at efds.fa.em5.oraclecloud.com](https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/65931?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)