Data Scientist

High blood pressure is the world's most common disease, causing 18 million deaths each year. At Hilo by Aktiia, our vision is a world where no lives are lost or damaged from the effects of high blood pressure. Our mission is to make this a reality by developing tech to help people control their blood pressure.

We are a venture-backed scale-up, having raised over $96M from investors in Europe and the United States. Our technology — rooted in 18 years of research at the Swiss Center for Electronics and Microtechnology (CSEM) — is the world's only medically accurate, continuous blood pressure monitor that is cuffless in daily life in the consumer space. Validated through extensive clinical trials and CE Marked as a Class IIa medical device, our solution is now available in 12 countries. In July, we launched in the US — a major step in bringing Hilo's technology to the millions of Americans living with high blood pressure.

We are a hybrid/remote-first company, headquartered in Neuchâtel, Switzerland, united by our passion for impact and innovation.

• Mine and analyse large-scale real-world data from Aktiia's databases to identify patterns, trends, and relationships related to clinical outcomes, product performance, accuracy, and usage
• Design, perform, and interpret statistical analyses of clinical study data, working with the clinical team on study endpoints, protocols, and appropriate analytical approaches
• Produce analytical results into clear scientific insights, publication-ready figures, and statistical summaries that support conference presentations, posters, and peer-reviewed publications
• Apply statistical and analytical methods to user and product data to answer questions around engagement, retention, conversion, feature usage, and segmentation
• Design, run, and interpret experiments and statistical tests to evaluate product or feature changes and quantify their impact
• Develop reproducible and traceable analytical workflows, with well-documented code, analyses, and results in line with quality and regulatory standards (ISO 13485, MDR, GCP). Contribute to our shared Python/SQL/Spark codebase through Git, CI/CD, and code review practices
• Select and apply appropriate statistical and modelling techniques to answer clinical, scientific, product, and business questions, assessing assumptions, limitations, and the reliability of results

• MSc (or equivalent demonstrated ability) in Data Science, Statistics, Bioinformatics, or another quantitative field
• 3–5 years of hands-on experience in Data Science, Statistics, Biostatistics, Data Analytics, or a related quantitative field. We care more about proven ability than an exact number of years, so strong candidates with less experience are very welcome to apply
• Strong proficiency in Python and SQL. Experience with Spark is a strong advantage.
• Strong statistical foundations, including hypothesis testing, regression, survival analysis, experimental design, and statistical modelling. Ability to select appropriate methods, assess assumptions and limitations, and interpret results clearly. An understanding of clinical study design and biostatistics is important
• Strong analytical problem-solving skills — you can translate ambiguous clinical, scientific, product, or business questions into well-defined analytical problems and identify appropriate approaches to answer them.
• Comfortable turning large, messy, real-world datasets into clear, publication-ready analyses and scientific figures
• Fluent in English, based in Western Europe, e.g. Switzerland, Spain, UK, France, Germany

Nice to have:

• Experience with advanced statistical modelling or predictive modelling
• Experience with Databricks and/or BI/dashboarding tools (Power BI, Tableau, Looker)
• Experience handling sensitive/clinical data and awareness of related regulations (GDPR, HIPAA)
• PhD in Data Science, Statistics, Bioinformatics, or a related field

• Hybrid/remote-first company
• High degree of autonomy
• Collaborate closely with clinical, scientific, product, and engineering teams