Clinical Data Analyst to join the Product team and become the analytical engine behind our next phase of growth. You’ll be the first full-time data hire, responsible for transforming real-world patient, clinical, and behavioral data into meaningful insights that drive product decisions, inform treatment strategies, and shape our approach to heart failure care. This is a hands-on opportunity ideal for someone passionate about research, eager to establish and innovate in a dynamic health tech environment.
🛠 What You’ll Do?
- Lead exploratory analysis of real-world clinical, behavioural, and device data — uncovering insights about both patient response and physician actions that inform protocol design, product evolution, and our broader treatment paradigm.
- Investigate patient trajectories, adherence patterns, notification dynamics, and treatment responses — identifying trends that guide decision-making and improve care strategies.
- Analyze clinician behaviour and intervention patterns in response to system recommendations, notifications, and patient trends.
- Collaborate with Product, Clinical, and R&D teams to frame questions, test hypotheses, and guide decision-making through data.
- Build reusable tools and metrics — such as time-in-range, notification classification, plan effectiveness — to support ongoing monitoring and cross-team alignment.
- Contribute to the creation of lightweight infrastructure and workflows that ensure analyses are reproducible, auditable, and scalable.
Must-Haves:
- 7+ years of experience in data analysis or applied data science, preferably in healthtech or clinical domains
- Fluent in exploratory analysis, with a strong ability to uncover patterns and generate hypotheses — not just build dashboards
- Expert in Python + Pandas, with strong command of Jupyter/Colab workflows
- Hands-on experience working with time-series physiological data
- Comfortable querying APIs and cleaning complex, semi-structured datasets
- Exposure to dbt, Streamlit, or similar lightweight dashboarding tools
- Passion for building early-stage infrastructure in a product-driven environment
- Strong analytical thinking, problem-solving skills, and the ability to communicate insights clearly across disciplines
Nice-to-Haves:
- Familiarity with clinical signal processing, or a demonstrated interest and ability to grow into applied data science for exploration purposes
- Comfort with light data engineering tasks (e.g., writing data loaders, schema validation)