The ideal candidate will be a curious self-learner with a proven track record of delivering value from routinely collected healthcare data or observational studies. You will provide health analytics and insights in various contexts, including Public Health, Pharmaceutical Research and Development, and Commercial/Payer and Patient Safety. Your responsibilities will include:
- Delivering and supporting advanced secondary analyses of data from EMR, claims, and primary observational data required by Therapeutic Area (TA) RWE strategies.
- Working comfortably in a rapid analytics environment alongside stakeholders to ideate appropriate and impactful analysis.
- Providing clear technical input, options, and directions to support strategic decisions made by AZ observational study teams on study design, data partner selection, and best practices in RWE data utilization.
- Monitoring work performed by contract personnel and vendors.
- Maintaining strong insight into the capabilities of potential external partners in RWE, especially for US and emerging markets.
- Demonstrating best practice in Real World Data Science across multiple domains and stakeholder groups.
Essential Skills/Experience
- Minimum of Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or related field.
- The duties of this role are generally conducted in an office environment. As is typical of an office-based role, employees must be able, with or without an accommodation to: use a computer; engage in communications via phone, video, and electronic messaging; engage in problem solving and non-linear thought, analysis, and dialogue; collaborate with others; maintain general availability during standard business hours.
Desirable Skills/Experience
- This is a hands-on role – so be excited to code!
- Enthusiastic about building on and learning new methods and ways to use real world data to change the practice of medicine.
- Demonstrated ability to build long-term relationships with stakeholders, understand relevant scientific/business challenges at a deep level, and translate into a programme of data science activities to deliver value to the business.
- Hands-on experience with EMR/Health IT, disease registries, and/or insurance claims databases with a minimum of 3 years.
- Experience with clinical data standards, medical terminologies, and controlled vocabularies used in healthcare data and ontologies (ICD9/10/SNOMED).
- Experience in supporting pharmacoepidemiology studies with a proven track record of advancing approaches with statistics/machine learning/data science.
- Ability to lead & manage multi-disciplinary data science projects.
- Proficient in SQL.
- Proficient in R or Python.