Senior Data Scientist – Prognostic and Health Monitoring (HUMS) Joby Aviation

Job Overview

Located in Northern California, the Joby Aviation team has been steadily working toward our goal of providing safe, affordable, fully electric air transportation that is accessible to everyone. Imagine an air taxi that takes off vertically, then quietly and quickly carries you over the congestion below, giving you back the time you’d otherwise spend sitting in traffic. Our team has been designing and flight testing this vehicle and is now seeing it through certification and high-rate production.

Joby Aviation is seeking a Senior Data Scientist to join our Health and Usage Monitoring Systems (HUMS) team. In this role, you will be driving algorithmic development behind the predictive health, safety, and reliability of our aircraft. You will partner closely with multidisciplinary Subject Matter Experts (SMEs)—across Propulsion, Flight Test, Battery Systems, and Structures—to design, develop, and deploy advanced algorithms that monitor the health and usage of critical Joby subsystems.

This is a senior individual-contributor role for an engineer who thrives at the intersection of physical systems and modern data science. You will own your projects end-to-end: translating complex physical degradation phenomena into robust predictive models, and turning those models into production-quality, well-tested code. If you are passionate about blending signal processing, machine learning, and data-engineering to shape the future of electric aviation, we want to talk to you.

What we bring to the table is a truly unique data landscape. You will not analyze flight data in a vacuum. Instead, you will integrate high-frequency flight sensor telemetry with comprehensive ground test data, component serial numbers, manufacturing database to construct a unified, definitive source of truth for aircraft health and component tracking.

To solve these complex challenges, we foster an innovative environment where you are actively encouraged to leverage the latest technologies and state-of-the-art AI frameworks to accelerate your work.

• Develop Health Algorithms:
  Design, build, and validate data-driven and physics-informed models to evaluate the condition, degradation, and Remaining Useful Life (RUL) of critical Joby subsystems (e.g., propulsion, batteries, actuation, and structures)
• Partner with Subject Matter Experts (SMEs):
  Collaborate closely with domain experts across Flight Physics, Aircraft Design, Flight Test, Reliability, and Systems Engineering to translate physical failure modes and structural loads into actionable diagnostics and prognostic algorithms
• Characterize Physical Behavior & Operational Loads:
  Deeply analyze aircraft physical behavior and actual operational loads by wrangling complex sensor and time-series data from flights, simulators, and subsystem test rigs. Use these insights to isolate anomalies, detect early faults, and map the long-term degradation of critical components
• Component Usage Tracking & Damage Modeling:
  Develop algorithmic frameworks to track component-level operating metrics, flight cycles, and life limits. Translate real-world operational loads into cumulative fatigue/damage models to monitor and inform fleet-wide asset component replacement
  Write Production-Grade Code:
  Turn prototypes into clean, well-tested, maintainable, and production-ready Python code. Participate in and actively raise the bar for team code reviews and engineering best practices
• Own Pipeline Architecture:
  Design, build, and own robust, end-to-end data pipelines and services that scale efficiently to process massive volumes of raw flight and test data
• Support Flight & Field Validation:
  Work alongside test engineers and technicians to validate and harden health-monitoring solutions using real-world physical tests
  Drive Tooling Innovation:
  Selectively evaluate and integrate advanced ML/AI methodologies (such as automated data labeling or diagnostic assistance tooling) where they genuinely accelerate Prognostics Health Monitoring (PHM) workflows and team efficiency

• MS or PhD in Aerospace, Mechanical, Electrical Engineering, Computer Science, or a related technical field
• 3+…