Senior Clinical Data Analyst

Description

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, behavioral, 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, alert dynamics, and treatment responses — identifying trends that guide decision-making and improve care strategies.
• Analyze clinician behavior and intervention patterns in response to system recommendations, alerts, 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, alert classification, plan effectiveness — to support ongoing monitoring and cross-team alignment.
• Design and validate pipelines for waveform-based clinical feature extraction, such as heart rate, respiratory rate, or rhythm irregularities, leveraging clean sensor data.
• Contribute to the creation of lightweight infrastructure and workflows that ensure analyses are reproducible, auditable, and scalable.

What will you do?

What do you need to bring with you?

Requirements

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 waveform analysis and clinical signal processing, or a demonstrated interest and ability to grow into applied data science work focused on extracting physiological features (e.g., HR, RR, AFib)
• Comfort with light data engineering tasks (e.g., writing data loaders, schema validation)