Head of Research

Description OneStep is looking for a Head of Research to lead the next generation of our motion and clinical intelligence platform. In this role you will lead the data science team and own the long-term strategy for how we extract value from our data. The team you'll lead sits at the heart of OneStep's product - owning the challenge of turning raw smartphone sensor signals into the gait parameters we compute from them, and going further to translate those parameters into real clinical impact for patients: biomarkers, predictions, and insights that shape how clinicians care for them. We're looking for someone who combines deep technical judgment with strong agency and creativity, a leader who proactively shapes the roadmap, spots opportunities in our data that others would miss, makes decisions and acts independently, and brings that same energy to the team they lead. Responsibilities Define and lead the team's roadmap across motion analysis, biomarkers, clinical prediction, and rehabilitation intelligence — aligned with product and business priorities. Own the data strategy. Define how we collect, model, and govern our data, ensuring what we capture today continues to create value years from now, and identifying what is missing in order to unlock new opportunities. Bring your own agenda. Continuously explore the data, generate hypotheses, and surface initiatives that create new value, both for the product and for the business. Stay hands-on. Dive into the data, prototype, and work alongside the team, not just direct from above. Lead and mentor the team while collaborating closely with product, engineering, clinical, regulatory, and commercial teams — building a culture of creativity, ownership, and independent thinking. Lead the modeling work that drives clinical impact. Build systems that estimate recovery, deterioration, fall risk, fatigue, and functional status from real-world motion data, and explainable, human-in-the-loop tools that help clinicians prioritize patients and adapt care plans. Own model evaluation, deployment, monitoring, and production reliability across real-world healthcare settings. Requirements Leadership experience. Experience managing and scaling high-performing data science teams. End-to-end ML maturity. Experience owning ML from ambiguous problem definition through deployment, monitoring, and iteration - including data pipelines, validation, evaluation frameworks (robustness, bias, calibration, generalization, clinical relevance), and production reliability. Cross-functional leadership. Ability to lead cross-functional work with product, engineering, clinical, regulatory, and business stakeholders, with strong communication skills to explain technical tradeoffs clearly. High ownership and agency. Brings initiatives proactively, makes decisions, and acts independently rather than waiting to be told what to work on. Creativity and intellectual curiosity. The kind of person who looks at a dataset and immediately starts asking "what else could this tell us?" Strong product and business sense. Comfortable thinking about user value, prioritization, and ROI, not just technical elegance. Advanced degree in ML, computer science, or an equivalent field. The following are a big plus Strong background in time-series ML, signal processing, sequence modeling, or longitudinal modeling - ideally with real-world noisy data from IMU, wearable, smartphone, physiological, behavioral, or clinical sources. Experience in digital health, healthcare AI, rehabilitation, biomechanics, medical devices, clinical research, or regulated products. Experience with digital biomarker development and clinical validation. Experience with gait analysis, IMU processing, activity recognition, motion capture, kinematics, or functional outcome measurement. Experience with longitudinal patient modeling, multimodal fusion, weak supervision, missing data, or partially observed labels. Experience with personalization, human-in-the-loop ML, or clinician-facing decision support.