Lead Data Scientist, Robotics

🕒 July 29

🏄 California, Oregon, +1 more states – Remote

🏄 California – Remote 🌲 Oregon – Remote 🔔 Pennsylvania – Remote

💵 $218k - $340k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Agility Robotics

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2017

📦 Logistics

🏭 Manufacturing

🔧 Hardware

Logistics • Manufacturing • Hardware

Agility Robotics is a leading manufacturer of mobile manipulation robots, known for their humanoid robot Digit. The company focuses on deploying its robots in commercial settings, such as material handling workflows, to enhance productivity across various industries including third-party logistics, manufacturing, and retail & eCommerce. With their innovative cloud automation solution, Agility Arc, these robots provide game-changing automation solutions. Agility Robotics aims to revolutionize labor by integrating humanoid robots in settings where meaningful work and economic value are crucial.

📋 Description

• Predictive maintenance & hardware reliability: Build models that predict MTBF and remaining useful life for specific components (actuators, cameras, compute, power systems). Partner with hardware engineering to model wear-and-tear under varying duty cycles, payloads, and environmental conditions, and turn those models into maintenance schedules and design feedback. • Fleet performance & RaaS unit economics: Analyze telemetry and logs to find which software versions, site conditions, or usage patterns correlate with the highest failure and intervention rates. Work with Product to define the "golden signals" of a RaaS deployment and stand up the dashboards behind each. Quantify the cost of human intervention (teleop, on-site support, manual recovery) and its drivers. • Root-cause & anomaly detection tooling: Build detection and RCA tooling that surfaces anomalies in fleet behavior early and helps engineers get from symptom to cause faster. • Manufacturing quality & feedback loops: Join end-of-line test data with field performance to find which manufacturing signals predict early field failures, and close the loop back to the factory to catch defects before they ship.

🎯 Requirements

• 10+ years applying data science / statistical modeling to real-world problems, with a track record of owning ambiguous, high-impact problems end to end. • Deep expertise in some combination of: reliability/survival analysis, time-series and anomaly detection, predictive maintenance, and causal/observational inference. • Strong software fundamentals — production-quality Python, comfort in SQL and modern data stacks. • 3+ years serving as a technical lead or the senior-most IC on cross-functional efforts, with a track record of setting technical direction for a team of data scientists/analysts, mentoring and growing ICs, and driving alignment across engineering and business stakeholders without formal authority. • Fluency partnering cross-functionally with hardware, embedded/software, manufacturing, and business/finance stakeholders, and translating analysis into decisions they trust. • Experience working with large-scale, messy, multi-modal operational data (sensor/telemetry, logs, event streams) and the judgment to know when the data can and can't support a conclusion. • Authorization to work in the USA.

🏖️ Benefits

• 401(k) Plan: Includes a 6% company match. • Equity: Company stock options. • Insurance Coverage: 100% company-paid medical, dental, vision, and short/long-term disability insurance for employees. • Benefit Start Date: Eligible for benefits on your first day of employment. • Well-Being Support: Employee Assistance Program (EAP). • Time Off: Exempt Employees: Flexible, unlimited PTO and 12 company holidays, including a winter shutdown. Non-Exempt Employees: 10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually. • On-Site Perks: Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations. • Parental Leave: Generous paid parental leave programs. • Work Environment: A culture that supports flexible work arrangements. • Growth Opportunities: Professional development and tuition reimbursement programs. • Relocation Assistance: Provided for eligible roles. • Annual Discretionary Bonus: Provided for eligible roles.