Need someone with strong R package development experience and familiarity with real-world datasets such as EMR, claims, and the OMOP data model. Proficiency in Git and Github
Biostatistics and Research Decision Sciences (BARDS) Epidemiology (EPI) Real-world Data Analytics and Innovation (RDAI) team is leveraging a Data Scientist responsible for developing Python/R software programs, documenting code and programming requirements to support research studies advancing real world data quality methodologies. Resource will need to be a SME in statistical methods, version control, and working with EHR claims and medical EHR data in the pharmaceutical industry.
Scope:
Develop internal analytic packages in R/Python to improve efficiency and the quality of in-house secondary data analytics. Resource will design and conduct data quality assessments for different indications and products of interest to the client. They will execute study protocol by developing reusable programming codes and building statistical models to generate data quality reports. He/she will also participate in the development of scientific publication
Responsibilities:
- Develop Analytic packages including commonly used analytic functions to apply to multiple in-house datasets across therapeutic areas.
- Developing and conducting proof-of-concept use cases across therapeutic areas
- Test usability and user access to the developed packages
- Document programming and code specifics, support the generation of related reports, and ensure proper version control during the development of the deliverables
- Pioneer and develop innovative statistical, machine learning
- (ML), and AI algorithms to distill insights from biological and healthcare datasets
- Expertise in data science (statistics, ML, AI, LLM, NLP)
- Engineering informatics, databases, web-development, programming in Python, R, SQL
- Experience in RWD, biology, genetics, epidemiology, neuroscience, immunology, etc.