Powering data driven insights that lead to better, faster decisions and therapies for patients by implementing new business technology solutions that solve significant scientific or business problems through the use and understanding of complex data.
Requirements
- Significant programming experience with SAS, SAS Macro, and SQL queries, or other programming for real-world data analytics (ie: R or Python), and working in data engineering platform environments such as Hadoop/AWS/CML/GiT.
- Experience and/or training in the application of advanced scientific and analytical methods.
- Proven implementation of creative technology solutions that advanced the business.
Responsibilities
- Conceive, design and implement new RWD business technology solutions that solve significant scientific or business problems through the integration, visualization, and analysis of large and complex data.
- Demonstrate high proficiency across a wide range of technologies related to the integration, visualization, and analysis of large and complex real-world data sets.
- Maintain broad expertise analyzing large real-world data including medical claims data, electronic medical records, survey data, etc.
- Demonstrate the ability to resolve key project hurdles and assumptions by effectively utilizing available information and technical expertise.
- Expand advanced methodology and adopt new technology capabilities such as machine learning, RWE dashboards and visualizations, automation, etc.
- Utilize knowledge of the pharmaceutical and healthcare business in the rapid advancement of agile, impactful, and cost-effective solutions.
- Proactively seek out new information and technologies in the literature/public domain and incorporate into individual project(s) as well as the overall program.
Other
- Acting as a lead data scientist in your project area, you will contribute RWD expertise to broader cross-functional initiatives.
- Candidates should be excited to drive innovation by implementing new business technology solutions that solve significant scientific or business problems through the use and understanding of complex data.
- Drive productivity and efficiency gains throughout multiple business areas.
- Highly autonomous and productive in performing activities, requiring only minimal direction from or interaction with supervisor.
- Understand and adhere to corporate standards regarding applicable Corporate and Divisional Policies, including code of conduct, safety, GxP compliance, and data security.
- Background in life sciences or work experience in the pharmaceutical industry preferred.
- Excellent written and oral English communication skills.
