Offer summary

Qualifications:

PhD in Biomedical Engineering, Data Science, Biostatistics, ML, or a related field with quantitative skills, or MSc with 2+ years of experience., Proficiency in time-series data analysis, signal processing, and scientific programming, preferably in R and Python., Strong communication skills to convey findings and contribute to scientific development., Passion for digital health and real-world evidence..

Key responsibilities:

Design and conduct scientific investigations using real-world biosensor datasets.

Clean, process, and analyze time-series data from wearable devices.

Collaborate on internal research and client-facing studies across various therapeutic areas.

Communicate results through reports, presentations, and publications.

Job description

Data Scientist – Digital Health

Remote (US only)

About VivoSense

VivoSense is a science-first digital health company building the future of patient-centered evidence through advanced biosensor analytics. Our software and scientific services enable the development, validation, and regulatory acceptance of digital biomarkers and outcomes grounded in real-world, real-life data. Since securing Series A financing, we are scaling up our research capabilities and expanding our reach across therapeutic areas and clinical development phases.

We help our partners—from leading pharmaceutical companies to cutting-edge research institutions—turn noisy, complex data into trustworthy evidence that accelerates drug development and improves health outcomes.

We don’t just analyze data—we build evidence.
Learn more: vivosense.com

What You’ll Do

Design and conduct scientific investigations using real-world biosensor datasets
Clean, process, and analyze time-series data from wearables (e.g., actigraphy, ECG, respiration, gait)
Collaborate on internal research and client-facing studies across therapeutic areas
Contribute to measure development, validation, and regulatory evidence generation
Translate noisy data into insight, impact, and clinical relevance
Communicate results through reports, presentations, and publications

About You

PhD in Biomedical Engineering, Data Science, Biostatistics, ML, or advanced degree with demonstrated quantitative skills (0–4 yrs post-PhD), or MSc with 2+ yrs hands-on experience
Skilled in time-series data, signal processing, and scientific programming (R and Python preferred)
Able to lead analysis on novel questions, communicate findings, and contribute to scientific development
Passionate about digital health, patient-centered outcomes, and real-world evidence

Bonus if you have:

Experience with clinical study data, wearable sensor data, regulatory submissions, or scientific publication

Additional benefits and perks