Orthopedic and Digital Solutions Medical Device Epidemiology and Real-World Data Sciences
Kelly is currently seeking a Sr. Epidemiologist for a long-term engagement with one of our Global Pharmaceutical clients. This position will be able to work remotely from home office. This person will join our Kelly FSP (Functional Service Provider) division, a managed solution provider and business unit of Kelly. This role is full-time and is offering full benefit options. As a Kelly FSP employee you may be eligible for Medical, Dental, Vision, 401K, and a variety of other benefits to choose from. You may also be eligible for paid time off, including holiday, vacation, and sick/personal time.
Section I: Position Summary
The team leads Real-World Data innovation and methodological excellence across our clients Medical Device sector and provides skills and expertise in using real-world evidence to support label extension, product development, safety, value demonstration for payers, and other activities. As a member of this highly-productive team, the Research Associate will have the opportunity to lead and co-author peer-reviewed manuscripts and conference presentations.
The Sr. Epidemiologist will be involved in addressing research questions related to medical devices using a variety of analytical techniques applied to an expanding array of databases. The person will be responsible for assisting with projects and initiatives in areas of epidemiology, comparative research, predictive analytics, health economics, post-market safety evaluation and surveillance, and regulatory label extension.
Section II: Principal Duties & Responsibilities
The role will involve participation in various project teams and task forces in addressing issues raised by product teams or regulatory agencies, to provide epidemiologic, predictive analytic and/or health economic consulting to product teams, generate needed real-world evidence, and/or disseminate scientific information through technical reports or models, presentations, and publications in peer-reviewed literature, as agreed by the team. Close collaboration with cross-functional teams involving market access, R&D leaders, data scientists, healthcare researchers, and healthcare providers is a key requirement of this position.
Examples of specific activities will include:
Leading or participating in projects to evaluate disease natural history, treatment patterns, patient journeys, safety and effectiveness of devices using clinical and surrogate endpoints, or benefit-risk questions for specific devices
Managing projects and timelines
Analyzing electronic healthcare databases such as electronic health records (EHRs), insurance claims data, hospital billing data, or registries
Developing, reviewing, and writing study protocols, analytical plans, and study reports
Conducting systematic reviews and meta-analyses
Preparing posters for presentation at scientific conferences
Participating in manuscript development, review and submission
Presenting research to internal stakeholders or external audiences
Participating in work streams / task forces to standardize research and analytical processes to improve efficiency and quality of deliverables
A minimum of a master’s degree in epidemiology, biostatistics, health services research, health policy and management, health economics or other related field is required
Experience with RWE Analytics
Experience working with large databases
Experience designing studies from an RWE perspective and help determine the best a patient criteria
At least 2 years of experience working in clinical research with a CRO or Pharms, Device company
This role does not need to have programming experience, but it is a nice to have
The candidate must have a sophisticated understanding of and the ability to analyze and interpret quantitative data using statistical software such as Stata, SAS, R, etc.
Experience with writing methods sections of study proposals/ protocols/ or background epidemiologic material on specific disease or therapeutic areas is required
The candidate must have strong written and verbal communication skills
Experience with predictive modeling and machine learning is a plus
Ability to collaborate and work as part of a team is required
The position will require under 10% of time in travel
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