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Lead Biostatistician
hace 2 meses
Aetion is a global leader in science-driven technology, utilizing real-world evidence to provide innovative healthcare solutions. We are seeking a highly skilled Lead Biostatistician to join our team in Barcelona, Spain.
Key ResponsibilitiesThe successful candidate will lead and support the design and execution of multiple projects, leveraging their expertise in biostatistics and causal inference methods to yield decision-grade real-world evidence from secondary data sources.
Key Responsibilities:- Applied Scientific Research: Lead and support the implementation of multiple studies, including real-world descriptive and comparative studies, and studies involving re-analysis of clinical trial data.
- Methodological Expertise: Maintain a strong knowledge base in pharmacoepidemiology, HEOR, and/or biostatistical methods as applied to observational RWE studies, as well as current healthcare databases used in these studies.
- Statistical Analysis: Support synthesis and preparation of statistical results for external presentations, and provide methodological support for study design across multiple therapeutic areas.
- Tool Development: Support the development of tools for automation, ensuring scalability of the Biostatistics team's analytics capabilities.
- Data Processing: Implement data processing pipelines and analyses.
- Software Development: Support software product development and validation.
- Knowledge Sharing: Support and promote educational activities and knowledge sharing, including developing best practices.
- Mentorship: Mentor early-career biostatisticians/epidemiologists in quantitative methods.
To be successful in this role, you will need:
- A PhD in biostatistics, statistics, epidemiology, or a related quantitative field, and at least 1 year of relevant experience conducting analytics with secondary real-world data sources.
- Extensive expertise in the design of observational/epidemiological studies, or relevant experience with clinical trial design and analysis.
- Extensive expertise in applying biostatistical and causal inference methods to yield decision-grade real-world evidence from secondary data sources.
- Proficiency in the R statistical programming language.
- Excellent communication skills, verbal and written.
- Proficiency in English is required.
- Ability to self-motivate.
- Resilient, collaborative, flexible, and innovative.
- Experience with Github.
Experience working in cross-functional teams, and experience with Databricks and Spark clusters are highly desirable.
