Associate Director in Data Science, Digital Health Analytics and Innovation (all genders)
Remote
Job Summary
Lead the identification, development, and deployment of novel digital endpoints and outcome measures across clinical trials and life cycle management programs. Develop and implement machine learning and data science methods to process multimodal time-series data generated by digital devices while ensuring scientific rigor and regulatory readiness. Advocate for the adoption of digital endpoints within the global R&D community and contribute to key regulatory filings and publications. Collaborate with the Global Digital Health organization to integrate emerging AI paradigms into digital health analytics.
Required Qualifications
- PhD in a quantitative discipline (e.g., data science, computer science, biomedical engineering, statistics, physics, or related field)
- Minimum of 7 years of relevant experience in the pharmaceutical, digital health, AI/ML or related industry
- Proven track record in designing and validating digital endpoints or biomarkers for clinical applications
- Hands-on experience processing and analyzing large-scale data streams from digital health technologies
- Experience in building machine learning pipelines for time-series and multimodal sensor data
- Strong expertise in digital biomarker/endpoint development
- Solid understanding of modern machine learning and AI methods
- Excellent stakeholder management skills
- English fluent
Desired Qualifications
- Experience with scalable data processing and ML frameworks (e.g., Python data ecosystem, distributed data processing, or cloud/HPC environments)
- Familiarity with generative AI and large language models
- Strong communication and scientific writing skills, enabling translation of complex technical content for diverse audiences
- Fluency in German is a plus
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