Data management, manipulation and analysis of existing real-world data sources (e.g. claims, registries etc.):
o Responsible implementing data management process, i.e. secure storage, logging and data destruction, across all secondary data studies
o Writing of programming code to address data manipulation, analysis and output requirements as detailed in the study protocol/ SAP, including quality control (QC) of all code and outputs, and post-review revisions, as per the agreed study timelines.
Co-ordination of resources
o Responsible for ensuring all secondary data studies are sufficiently resourced from a statistical/ analytical perspective, including liaison with other senior members of Gen SP team to align on team capacity/ workload.
The person
Substantial experience and proficient in using statistical software (e.g. Stata, SAS, SPSS etc.)
Substantial experience of conducting data manipulation and analysis of large, complex, event-level secondary data sources (e.g. claims data, electronic medical records, administrative data, registries etc.)
Hold a good honours degree (2:1 or 1st) in a numeric/ analytical discipline
Experience of contributing towards or developing study protocols and/or SAPs
Knowledge of the pharmaceutical industry
A high level of interpersonal skills and willing to work collaboratively as part of a wider team
A drive to help shape the future structure and success of the S&DA team
Highly motivated with a proactive approach to work and strong problem-solving skills.
A high level of numeracy, analytical, and interpretive skills, with a close attention to detail
Good organisational and time management skills and a flexible way of working
Strong written and verbal communication skills and a confident communicator
Proficient in standard Microsoft packages, e.g. Word, Excel and PowerPoint.
The following attributes are not considered essential, but would be preferable in candidates:
Substantial experience and proficient in Stata statistical software
- Experience with, or knowledge of, real-world evidence and/or observational studies
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