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Hilo by Aktiia is a venture-backed medtech scale-up (€96M+ raised) developing the world's only medically accurate, cuffless continuous blood pressure monitor. The company is headquartered in Neuchâtel, Switzerland, and operates as a hybrid/remote-first organization across Europe and the US.
You will serve as a Data Scientist, taking ownership of analytical questions spanning clinical, scientific, product, and business domains. This is a hands-on, autonomous role where you will independently manage the full analytical lifecycle—from data preparation through statistical analysis, interpretation, and communication of findings.
Key responsibilities include:
- Mining and analyzing large-scale real-world and clinical datasets from Aktiia's databases to identify patterns, trends, and relationships related to clinical outcomes, product performance, accuracy, and usage
- Designing, performing, and interpreting statistical analyses of clinical study data in collaboration with the clinical team
- Producing publication-ready figures, statistical summaries, and scientific insights that support peer-reviewed publications, conference presentations, and posters
- Applying statistical and analytical methods to user and product data to answer questions around engagement, retention, conversion, feature usage, and segmentation
- Designing, running, and interpreting experiments and statistical tests to evaluate product or feature changes and quantify their impact
- Developing reproducible, well-documented analytical workflows in Python/SQL/Spark with Git, CI/CD, and code review practices, adhering to quality and regulatory standards (ISO 13485, MDR, GCP)
- Selecting and applying appropriate statistical and modeling techniques while assessing assumptions, limitations, and result reliability
- Collaborating effectively across clinical, scientific, product, and engineering teams to communicate findings to both technical and non-technical audiences
You will be successful if you can independently translate ambiguous analytical questions into well-defined problems, produce reliable and reproducible results, generate insights that drive scientific publications and informed decision-making, and communicate complex findings clearly across diverse stakeholders.
