Senior Manager, Real World Science
Alexion Pharmaceuticals
- Dublin
- Permanent
- Full-time
- Deliver/Implement and support advanced secondary analyses of data from EMR, claims and primary observational data required by Therapeutic Area (TA) RWE strategies
- Comfortable working in a rapid analytics environment alongside stakeholders to ideate appropriate/impactful analysis along with implementation
- Provide 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
- Monitor work performed by contract personnel and vendors
- Maintain a strong insight into the capabilities of potential external partners in RWE, especially for US and emerging markets.
- Demonstrate best practice in Real World Data Science across multiple domains, and/or stakeholder groups.
- Minimum of Master's degree in Computer Science, Statistics, Mathematics, Data Science, or related field with at least 3 years in the pharmaceutical industry, biotechnology, or consulting environment.
- 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.
- 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 partners , 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
- Experience with in clinical data standards, medical terminologies and controlled vocabularies used in healthcare data and ontologies (ICD9/10/SNOMED)
- Experience in supporting pharmacoepidemiology studies with 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 at least one of R, Python or SAS