Data Operations Lead

About Holosis Health

Holosis Health is building the next generation of care intelligence for high-risk patients, powered by AI-driven sensing technology.

We are pioneering continuous, non-invasive monitoring that transforms everyday data into meaningful clinical insights, helping providers intervene earlier, reduce hospitalizations, and improve outcomes.

Led and backed by seasoned entrepreneurs with a proven track record, Holosis combines startup energy, cutting-edge innovation, and a bold mission to reshape how chronic care is delivered.

The Role

We are seeking a highly motivated Data Operations Lead to own and lead our data collection, monitoring, testing and troubleshooting operations. This role is central to building and orchestrating our end-to-end and data workflows, including monitoring, testing and QA, data acquisition, analysis, cleaning, management, and annotation.

You will serve as a key bridge between real-world data and our Algorithm, Software, and Product teams. The ideal candidate brings hands on technical capabilities as well a managerial and coordination skills, with the ability to lead, build, and orchestrate multiple parallel activities across the organization, acting as the operational “gatekeeper” for data quality and reliability.

Key Responsibilities

• Design, coordinate, and orchestrate data collection activities that support R&D needs.
• Own the testing and QA processes across systems and deployments.
• Develop Python-based tools for data collection, visualization, calibration, and analysis.
• Own the full monitoring and troubleshooting flow for production-deployed systems, identifying data anomalies and system issues.
• Investigate failures and anomalies, track issues, and drive root-cause analysis to resolution.
• Collaborate closely with Algorithm Software and clinical teams to ensure accurate and reliable data capture and reporting.
• Own and oversee the data annotation pipeline.
• Lead a team responsible for data collection, annotation, and testing.
• This is a hands-on role, not a purely managerial position - you are expected to actively design, build, run, and improve data related activities.

Required Skills & Qualifications

• Academic background in Biomedical Engineering, Life Sciences, Medicine, or a related discipline.
• Proficiency in Python, with demonstrated hands-on experience in building tools or workflows.
• Strong managerial and organizational capabilities, with proven leadership experience in industry and/or military service.
• Solid background in data handling, including collection, processing, analysis, and visualization, with a deep understanding of data quality and structure.
• Excellent communication skills for effective collaboration across teams and for working directly with study participants.
• Prior experience in experimental data collection is a strong plus.
• Experience with clinical or physiological data is an advantage.