В крупную фармкомпанию Novartis требуется RWE Manager.
The Real World Evidence (RWE) Manager is responsible for the scientific and methodological aspects of all RWE projects as well as providing guidance for other members of the team.
Your responsibilities include, but are not limited to:
- Produce analytic deliverables, including full study reports for RWE or observational database analyses projects
- Perform project management by coordinating project activities and timelines as well as issue management
- Independently draft and edit documents such as high level research proposals, protocols and statistical analysis plans
- Develop project timelines together with the Medical Team
- Perform in-depth research and quantitative and qualitative analysis independently
- Seek out opportunities for the development of new RWE services and new customers within Novartis
- Maintain familiarity with technical developments in RWE, epidemiological and data science fields
- Regularly elicit customers' satisfaction levels with Data Science's RWE services. Identify service areas requiring attention
What you’ll bring to the role:
- Bachelor’s degree plus 3+ years conducting scientific research in the pharma industry, contract research organization, or academic institute; or experience in a closely related discipline within the pharma industry (e.g., clinical research, statistics, epidemiology). Or Master’s degree in a field such as medicine, epidemiology, biostatistics, statistics, bioinformatics or similar. And 2+ years of experience conducting scientific research in the pharma industry, contract research organization, or academic institute; or experience in a closely related discipline within the pharma industry
- Preferable experience in the application of statistical methods to the analysis of observational data
- Preferable technical proficiency in analytical and visualization tools and statistical programming languages
- Deep knowledge of RWE data sources and standards
- Preferable expertise in applied statistics. Experience in the application of statistical methods for analysis of observational data including propensity scores, sensitivity analyses, etc. is a plus
- Good understanding of organizational processes. Extensive experience working cross-functionally with key internal stakeholders
- Open to experimentation and taking smart risks to support creative thinking that leads to practical solutions to healthcare and business challenges
- Holds a high standard on quality excellence