Project Manager Clinical Data Science

Main Responsibilities

• Algorithm development and validation, such as machine learning-based classification or prediction algorithms in clinical contexts
• Development of dashboards or other visualizations for real-time tracking and insight into ongoing study-related activities
• Development, implementation and optimization of codes / programming for statistical analysis according to SAPs as well as creation of TLFs
• Development of statistical analysis plans, monitoring statistics, sample size (re-) estimation as appropriate for complex clinical research projects
• Guide stakeholders in defining their data analysis objectives
• Development and implementation of concepts (including utilization of AI) for general process improvements and innovation in clinical research
• Provide input for statistical reports and support publications for clinical research projects

Additional statistical activities:

• Statistical and data science consultancy, including model and data interpretation, for Project Managers and Principal Investigators
• Simplify and translate complex statistical and machine learning analyses for non-technical stakeholders through visualizations and clear summaries.

Main Requirements

• MSc degree in Data Science, Bioinformatics, Statistics, Machine Learning, Computer Science, or closely related field
• Strong programming skills (preferably SAS), with experience in handling large, complex clinical datasets
• Advanced skills in data analysis, including predictive modeling, machine learning, and diagnostic accuracy analyses
• Strong understanding of statistical concepts and experience applying them in real-world research or clinical data contexts
• Strong analytical skills with the ability to use data to drive decision-making and measure process success
• Familiarity with clinical data standards (e.g., CDISC, SDTM)
• Knowledge in project management software (e.g., MS Project, JIRA) and clinical data management tools
• Attention to detail and reliability
• Flexibility and customer-focused mindset
• Collaborative and team-oriented with the ability to work cross-functionally
• Fluency in English

• An interesting and varied job in an exciting and innovative organization
• The opportunity to be part of a highly committed international team
• Modern infrastructure
• High degree of flexibility regarding working hours and location (depending on operational requirements)
• Generous pagacke of social benefits, including supplementary vacation days and pension scheme contributions
• Internal skills training opportunities and support for continued education

Compétences idéales

• Bioinformatics
• Data Visualization
• Machine Learning
• Predictive Modeling
• SAS

• Zizers, Grisons, Switzerland

Expérience professionnelle

• Data Engineer
• Data Analyst
• Data Scientist

Compétences linguistiques

• English