The Real World Healthcare Data Analyst/Scientist conducts observational database studies using various sources of healthcare data to support R&D projects at various stages of drug development and lifecycle management. These include specific epidemiology, health outcomes and other observational studies to better understand disease natural history, incidence/prevalence, co-morbidities, treatment patterns, and health and safety outcomes in ‘real world’ patient populations.

The Real World Healthcare Data Analyst/Scientist is expected to be an expert within the Observational Analytics team and provide leadership to the group and the Analytics and Data Sciences (ADS) department overall.  This person has an in-depth understanding of multiple types (e.g. claims, EMR/HER, disease registry) and sources (e.g. Optum, CPRD) of real world data (RWD). This person works directly with Observational Analytics (OA) leadership to recommend policy and standards and develop new techniques and strategy for data handling, retrieval and reporting to support all aspects of the ADS and ADS Epidemiology activities and RWD initiatives. This person can act as a mentor for the junior OA team members with some project management responsibilities. The ADS OA team keeps up with trends in the industry and regulatory environment in order to assist Biogen and ADS in creating processes and tools to stay ahead of the competition.

Principal Accountabilities:

• Collaborate with ADS epidemiologists and Global Safety physicians to provide statistical programming, systems analysis and database management support for observational studies/projects using internal observational health related database resources. Ensure each research project is delivered on time, to protocol specifications and high quality standards
• Analyze, design, develop, test, implement, validate document, and maintain effective and efficient computer solutions, tools, and database systems for conducting, analyzing and reporting observational database studies
• Contribute to development and maintenance of standards for program development and validation, and for data storage, quality, and reporting.
• Provide technical user/project support and consulting services on programming and database support activities/issues
• Assist in database evaluation and selection activities as needed.

The key requirement is demonstrated knowledge using Real World/Observational Health related data & Epidemiologic industry practices, techniques, and standards.

Experience:

• Bachelor’s Degree, Master’s preferred, in biological sciences, medically related field or computer/database related field.
• 5+ years direct experience using observational data in the healthcare/biotech/pharmaceutical industry. Expert SAS user. Experience managing, developing and training other analysts. Strong understanding of multiple healthcare claims and electronic healthcare records database. 5+ years’ experience working in a pharmacoepidemiology or health economics department. Machine learning, R, and python skills highly preferred. 

Technical/Software skills: 

• Knowledge office systems such as MS Word, MS Excel
• Knowledge of relational databases and database concepts
• Database design and data modeling techniques
• Familiarity with SQL
• Expert SAS Programming experience
• Machine learning, R, and python skills preferred 
• Knowledge of data analysis and trending
• Familiarity with statistics

Non-technical skills:

• Senior staff should have strategic vision in addition to operational excellence and demonstrate the following qualities; Analytical, Forward looking, Insightful, Intuitive
• Excellent communication skills
• Strong presentation skills with presentations to both large and small audiences.
• Strong project management skills including managing multiple projects across multiple functional areas.
• Excellent analytical and problem-solving skills in a dynamic environment.
• Demonstrated ability to learn and embrace new technologies, applications and solutions

The Real World Healthcare Data Analyst/Scientist conducts observational database studies using various sources of healthcare data to support R&D projects at various stages of drug development and lifecycle management. These include specific epidemiology, health outcomes and other observational studies to better understand disease natural history, incidence/prevalence, co-morbidities, treatment patterns, and health and safety outcomes in ‘real world’ patient populations.