Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.About The Role Agility Robotics builds Digit, a humanoid robot deployed into real warehouses and factories under a Robots-as-a-Service (RaaS) model. Every hour Digit operates generates telemetry, logs, sensor streams, and maintenance events — and turning that into reliability, unit economics, and product decisions is the job. As a Senior Staff Data Scientist, you'll define how we use data to build better robots and make better decisions. This is a high-impact, high-visibility role where you'll set the technical direction for analytics and modeling while helping build a truly data-driven engineering organization. In this newly created role, you'll transform massive volumes of complex robot data into the insights and models that drive decisions across hardware, software, manufacturing, and operations. You'll create the foundation for how we measure success, improve robot performance at scale, and prioritize what to build next — accelerating how we design, deploy, and continuously improve our autonomous systems. About The Work 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 Beyond the original charter, you may also help shape: Experimentation & fleet A/B — a framework for safely rolling out software/firmware changes across a physical fleet and measuring impact on performance, reliability, and intervention cost. Data quality & instrumentation strategy — partnering with embedded/software teams to define what gets logged and at what fidelity, so the data needed for these models exists in the first place. Demand/capacity & deployment economics — models that inform fleet sizing, spares/inventory, and the economics of new site rollouts. Safety statistics. About You 10+ years applying data science / statistical modeling to real-world problems, with a track record of owning ambiguous, high-impact problems end to end. MS or PhD in Statistics, Computer Science, Operations Research, Engineering, Physics, or a related quantitative field; or equivalent professional experience. PhD and coursework/experience in reliability engineering, survival analysis, or applied statistics preferred. Prior work in robotics, autonomous systems, hardware, IoT/connected devices, industrial, or manufacturing settings. 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 a senior 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 Bonus Points Familiarity with fleet operations, RaaS/subscription unit economics, or SRE-style operational metrics. Exposure to manufacturing quality systems (end-of-line test, SPC, yield/defect analytics). Location This is a fully remote role with the option to work hybrid if a commutable distance from our Salem, OR, Pittsburgh, PA, or Fremont, CA offices. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.Anticipated Base Salary Range$218,000—$340,000 USDIn addition to base pay, our competitive total rewards package consists of the following for full-time employees: 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. All of our roles are U.S.-based. Applicants must have current authorization to work in the United States. Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment. Agility Robotics does not accept unsolicited referrals from third-party recruiting agencies. We prioritize direct applicants and encourage all qualified candidates to apply directly through our careers page. If you are represented by a third party, your application may not be considered. To ensure full consideration, please apply directly.