Senior Data Engineer / Senior Data Scientist

We are seeking a highly motivated and skilled Data Engineer / Data Scientist to join our internal study teams and support the operational backend of our digital biomarker platform. This individual will play a key role in developing, optimizing, and maintaining robust operational data analysis pipelines that ensure the quality, integrity, and reliability of digital biomarker data collected during customer clinical trials. The successful candidate will bridge the gap between biomedical data collection and clinical operations, enabling data-driven decision-making and proactive study management.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Biomedical Engineering, or a related quantitative field
• 3+ years of experience in Data Engineering, Data Science, or a similar role, preferably in healthcare, biomedical, or clinical research environments
• Strong Python skills (Pandas, NumPy, software development best practices)
• Proficiency in SQL and experience working with complex datasets
• Hands-on experience with AWS or other cloud platforms
• Experience working with high-volume time-series data (sensor data, device logs, patient activity data)
• Strong analytical, problem-solving, and communication skills

Nice to have:

• Experience with clinical trials, ICH-GCP, CDISC, HIPAA, GDPR, or 21 CFR Part 11
• Knowledge of digital biomarkers, wearable technologies, or biomedical data analysis
• Experience with dashboarding and visualization tools such as Plotly Dash or Power BI
• Experience with statistical analysis or machine learning in healthcare or biomedical applications

• Develop and maintain operational data analysis pipelines using Python and SQL for clinical study monitoring
• Generate real-time metrics related to patient adherence, device performance, data quality, and protocol compliance
• Build scalable pipelines for high-volume time-series data from wearables, sensors, and mobile applications
• Optimize data infrastructure for performance, reliability, and cost-efficiency in a regulated environment
• Create automated dashboards and reports to support clinical operations and proactive study management
• Collaborate with Clinical Integration, Workflow, and Digital Biomarker Science teams to translate operational needs into technical solutions
• Support internal stakeholders and external clients with operational analytics and data flow expertise
• Document pipeline architecture, data flows, and analysis methodologies