Senior Staff Data Scientist, Robotics

Agility; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Agility is seeking a Senior Staff Data Scientist to define how fleet data becomes reliability insight, product prioritization, and deployment economics for a Robots-as-a-Service business.

The role focuses on telemetry, logs, sensor streams, maintenance events, predictive models, and decision systems at scale. You will work on predictive maintenance, anomaly detection, and data-driven improvements across the robotics fleet.

Qualifications

• Experience with real-world robotics or IoT systems.
• Ability to derive decisions from messy operational data.
• Expertise in reliability analysis, time-series, anomaly detection, predictive maintenance, or causal inference.
• Strong Python programming for production environments.

Responsibilities

• Build predictive maintenance and remaining-useful-life models for robot components.
• Analyze fleet telemetry to connect software versions, site conditions, and usage patterns with intervention rates.
• Define golden signals for RaaS deployments with product and operations teams.
• Create anomaly detection, root-cause tooling, and feedback loops between manufacturing and field operations.

Skills

Senior data science

Statistical modeling

Production Python

Time series

Anomaly detection

Tools

Python

Job description

What the role actually is

Agility is hiring a senior staff data scientist to define how Digit fleet data becomes reliability insight, product prioritization, and deployment economics. The listing focuses on telemetry, logs, sensor streams, maintenance events, predictive models, and decision systems for a Robots-as-a-Service business.

The role is newly created and explicitly tied to robot performance at scale. It spans predictive maintenance, anomaly detection, manufacturing feedback loops, fleet A/B testing, and the instrumentation needed to measure real-world robot behavior.

What you would work on

• Build predictive maintenance and remaining-useful-life models for robot components
• Analyze fleet telemetry to connect software versions, site conditions, and usage patterns with intervention rates
• Define golden signals for RaaS deployments with product and operations teams
• Create anomaly detection, root-cause tooling, and manufacturing-to-field feedback loops

What they are asking for

• Senior data science or statistical modeling experience on ambiguous real-world systems
• Background in robotics, autonomous systems, hardware, IoT, industrial, or manufacturing environments
• Expertise in reliability analysis, time series, anomaly detection, predictive maintenance, or causal inference
• Strong production Python and comfort translating messy operational data into decisions

Why this one is worth a look

Fleet telemetry is where deployed robots start teaching the company what actually works. This role belongs on the board because it turns real humanoid operations into the measurements that shape reliability, product roadmap, and customer economics.