Senior Data Scientist, MedTech R&D – Hybrid & Growth

Sonova; Stäfa; Hybrid; CHF 120,000 - 180,000; Full time

Job summary

Sonova in Switzerland is seeking a Senior Data Scientist to develop data-driven models using large-scale real-world data. You will analyze, structure and interpret complex datasets focusing on usage analytics to generate insights and enable innovative features in a MedTech environment.

You will join an interdisciplinary R&D team in an agile setup, collaborating with engineers, researchers and product teams to apply machine learning and statistics to health-related data, build data catalogs and

Qualifications

• 4–5+ years of experience as a Data Scientist or in a similar role.
• Degree in a quantitative discipline; PhD preferred.
• Strong programming skills in Python.
• Solid background in machine learning, statistics and data analysis.
• Experience working with large datasets and data pipelines.
• Structured, analytical and solution-oriented mindset.
• Ability to translate complex analyses into clear insights for technical and non-technical audiences.
• Strong communication skills and team orientation.
• Knowledge in audiology or health sciences is a plus.
• Fluent English skills.

Responsibilities

• Develop and improve data-driven models based on large datasets.
• Analyze and evaluate real-world evidence data to generate insights.
• Apply machine learning and statistical methods to health-related data.
• Contribute to data creation, validation and feature engineering; support data catalogues.
• Collaborate in interdisciplinary agile R&D teams.
• Stay up to date with latest research, tools and methodologies.

Job description

Sonova in Switzerland is seeking a Senior Data Scientist to develop data-driven models using large-scale real-world data. You will analyze, structure and interpret complex datasets focusing on usage analytics to generate insights and enable innovative features in a MedTech environment.

You will join an interdisciplinary R&D team in an agile setup, collaborating with engineers, researchers and product teams to apply machine learning and statistics to health-related data, build data catalogs and