Lead Data Manager

The Laboratory for Intelligent Global Health and Humanitarian Technologies (LiGHT) at EPFL is seeking a Lead Data Manager to build and oversee all data management activities in the Lab. This is a unique opportunity to shape the lab's data architecture, pipelines, and governance from the ground up, supporting major AI-for-health initiatives and complex multinational clinical trials. Mission, * Lead and oversee all Data Management (DM) activities across LiGHT's research portfolio, including complex multicountry clinical trials in Africa and AI-based health innovation projects.

• Develop, implement, and continuously refine the LiGHT Data Management and Data Governance framework, integrated within the EPFL ecosystem and compliant with GCP, GDPR, DPDP (India) and relevant data protection regulations.
• Act as the focal point and accountable lead for all data management and compliance-related matters in LiGHT's role as Sponsor or Coordinating Centre within international consortia.
• Develop and maintain all SOPs, work instructions, templates, and forms related to data management, biostatistics, and data governance.

Data Architecture & Infrastructure

• Design, implement, and maintain secure, scalable data architectures for clinical and AI research projects, including EDC systems, data lakes, and integration pipelines.
• Oversee the design & integration of eCDS solutions and ensure interoperability across databases, AI model repositories, and analytics environments.
• Liaise with EPFL IT and research data offices to ensure alignment with institutional standards and data security policies.

Data Science & AI Integration

• Lead the development of data pipelines for AI model training, validation, and deployment, including data curation, annotation, quality assurance, and metadata governance.
• Develop data-driven dashboards, monitoring systems, and automated pipelines for data analysis and visualization.
• Support the development of AI-ready datasets, ensuring proper data provenance, consent tracking, and harmonization across sites.
• Work closely with data scientists and engineers on machine learning model governance, versioning, and reproducibility.

Operational Oversight & Mentorship

• Coordinate and supervise contractual data managers, data scientists, and external CROs or IT partners, ensuring timely and high-quality deliverables.
• Develop and maintain contractual and quality oversight mechanisms, including vendor assessment and performance tracking.
• Mentor students, junior researchers, and collaborators in data management, reproducible research, and ethical data practices.
• Support scientific reporting, donor communications, and publications based on LiGHT datasets.

Partnerships & Innovation

• Explore and establish strategic collaborations with external partners in academia, industry, and global health to strengthen LiGHT's data science ecosystem.
• Stay abreast of emerging trends in AI, data standards (e.g., CDISC), FAIR data principles, and federated learning for global health research.

• PhD (preferred) or Master's degree in data science, computer science, biomedical informatics, or a related quantitative field
• Minimum 5 years of experience in data management, data engineering, or applied data science, including leadership in global health or clinical research.
• Demonstrated experience managing distributed data workflows in LMIC and multi-institutional research environments.
• Proven proficiency in all aspects of clinical data management, including database setup, CRF design, edit check programming, data validation, query management, SAE reconciliation, coding, data review, and database lock.
• Experience establishing and maintaining Data Quality Management Systems (QMS) for research environments.
• Proven experience managing data management subcontracts and oversight of external vendors or CROs.
• Strong understanding of data versioning, lineage tracking, and reproducibility standards, including Git-based workflows and CI/CD integration.
• Proficiency in Python
• Familiarity with CDISC, GxP standards, and international research data compliance with a strong foundation in data security and compliance, including GDPR and emerging frameworks like India's DPDP Act (2023).
• Demonstrated contribution to open-source or FAIR-compliant data infrastructure projects.

Preferred

• Familiarity with medical LLM applications or clinical decision support systems
• Experience with safety-critical evaluation protocols (e.g., benchmark leakage detection, hallucination profiling, audit trails)
• Deep interest in equity-centered deployment and global health implications of LLMs
• Experience with federated learning, synthetic data generation, or privacy-preserving AI.
• Familiarity with cloud environments (AWS, GCP, Azure) and HPC orchestration.
• Exposure to real-world evidence generation or digital health analytics in LMIC settings.

• Mission-driven work at the intersection of technology, health, and global equity
• Opportunity to shape open-source platforms used by WHO, ICRC, and other partners
• A creative, ambitious, and collaborative team across continents

Competitive salary and benefits, aligned with experience and location

EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main missions of the institution: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 17,000 people, including over 12,500 students and 4,000 researchers from more than 120 different countries., The Laboratory for Intelligent Global Health and Humanitarian Response Technologies (LiGHT) https://www.light-laboratory.org/ is an impact-driven research group creating novel AI tools specifically adapted to limited-resource and volatile global health settings and bringing them to scaled, locally owned implementation. It is based at the Swiss Institute of Technology (EPFL) - In the top 10 computer science institutions globally, EPFL is a deeply international hub for technical excellence in AI. Our mission is to develop safe, scalable, and context-aware digital health tools. We work with international NGOs such as WHO, MSF, ICRC, and national ministries of health to design, create, validate and deploy trustworthy AI in real-world healthcare systems""especially in settings where clinical resources are limited and stakes are high.