This will be a senior position at the recently created Center for Excellence in Respiratory Pathogens (CERP) based in Lyon, France. The CERP develops evidence generating research to support decision making related to respiratory pathogens within the Civil Hospitals and the University Claude Bernard in Lyon. The CERP’s missions are: i) to create excellence in multi-disciplinary research combining virology, epidemiology, analytics, biocomputing and modeling; ii) to ensure a continuum from data collection (surveillance & capacity building) to data use for policy making (analytic, modeling, and external engagement); iii) to be a convener for major international stakeholders working on this thematic and to develop public-private instruments to ensure synergies. The CERP is part of the Centre International de Recherche en Infectiologie (CIRI: https://ciri.ens-lyon.fr/), which is a joint research unit of the University Claude Bernard, Inserm, CNRS and the École Normale Supérieure in Lyon, in partnership with VetAgro Sup, Institut Pasteur and the Civil Hospitals in Lyon.
This position will be key to develop the CERP’s activities around the use of real-world evidence and advance analytics to support the different studies and projects. It will be expected of this expert to maintain up-to-date knowledge of real-world data assets and analytical methods in order to develop innovative projects and provide expert advice and support. This expert will be expected to contribute to the establishment of the vision of the CERP by applying his/her scientific and technical skills to support the implementation of the CERP’s strategy by identifying gaps and challenges in key areas and propose innovative solutions to address them. This is a unique opportunity for a data scientist to join a new motivated and experienced research team in an international working environment to address key challenges in health surrounding respiratory diseases. This expert will work collaboratively to create high-quality innovative analytical products and can benefit from a wealth of large databases, study platforms and from external partnerships with other academic, governmental and industry partners.
Ideally, the candidate must combine strong epidemiological expertise and analytical skills, and good understanding of infectious disease epidemiology.
Description of duties
• Lead a data driven scientific research portfolio, including project conceptualization and innovative designs.
• Lead and support research analytical projects based on real-world evidence.
• Lead analysis of epidemiological and healthcare data, including clinical trial datasets and electronic health records, using established and novel statistical and analytical techniques.
• Propose and create solutions by identifying novel approaches to address analytical and data gaps.
• Lead and contribute to the write-up of manuscripts for publishing in high-impact peer-reviewed journals, of abstracts and presentations for international conferences, as well as of technical and study reports.
• Co-supervise maters and PhD students.
• Share expertise proactively by communicate complex concepts and interpretation of analysis and findings to different audiences, including students, clinicians, policymakers, and health economists.
• Provide internal support to colleagues in other research areas.
• Work collaboratively across the different CERP areas and with external collaborators and stakeholders.
• Actively manage project activity and timelines.
• Represent the CERP at external meetings.
Required education and work experience
• PhD in a quantitative subject (e.g. computer science, data science, statistics, mathematics, biostatistics, biomedical engineering, epidemiology) or equivalent combination of education, training and experience.
• A minimum of 5 years of relevant experience in academia, public health, biotechnology and/or pharmaceutical industry.
• Advanced experience in R and other programming languages (e.g. Python, SQL, advanced Microsoft Excel using Visual Basic for Application, SAS).
• Expert knowledge of causal inference theory.
• Experience in interpreting and presenting complex analyses and findings.
• Experience in statistical methods to investigate real-world problems (e.g. data modelling, predictive analytics and time to event analysis).
Desirable education and work experience
• Experience in applying machine learning techniques.
• Experience in preparing, analyzing and managing large healthcare datasets from observational non-interventional and/or interventional studies.
• Academic experience, with rigorous scientific standards.
Skills
• Fluent in spoken and written English. Intermediate knowledge of French is desirable.
• Excellent written and oral communication skills.
• Systematic approach to problem solving, including identification of root causes and solutions.
• Integrity.
• Scientific excellence.
• High level of self-awareness.
• Ability to cooperate cross-functionally.
• Able to identify multidisciplinary solutions and recommend a course of action to support multiple functions on decision making.
• Good foresight and judgement and able to work independently.
• Enthusiastic and professional approach to working with colleagues, and external collaborators.