Biostatistical Programming Senior Manager

• Provide technical solutions to programming problems within the Centre for Observational Research (CfOR)
• Lead and develop technical programming and process improvement initiatives within CfOR
• Represent the programming function and participate in multidisciplinary project team meetings
• Project manage programming activities, according to agreed resource and timeline plans
• Ensure programming activities adhere to departmental standards and SOPs
• Write and/or review and approve programming plans
• Write and/or review and approve analysis dataset specifications
• Review and approve key study-related documents produced by other functions, e.g. SAPs, CRF, Data Management Plan, etc.
• Write, test and validate software programs in Unix to produce analysis datasets and presentation output, to be included in reports for submission to regulatory agencies, publications and other communications
• Write, test, validate and execute department-, product- and protocol-level macros and utilities
• Oversee the work of outsourced resources assigned to projects
• Lead and/or participate in the development and review of CfOR policies, SOPs and other controlled documents
• Participate in study and systems audits by Clinical Quality Assurance (CQA) and external bodies, and respond to audit questions and findings
• Participate in the recruitment of programming staff
• Actively participate in external professional organizations, conferences and/or meetings
• Provide input to and participate in intra-departmental and CfOR meetings
• Contribute to the continuous improvement of programming, CfOR, and Research and Development (R&D)
• Manage staff performance and oversee staff assignments and utilization

• Doctorate degree and 2 years of Computer Science, Statistics, Mathematics, Life Sciences, Economics or other relevant scientific subject
• Master’s degree and 8 to 10 years of Computer Science, Statistics, Mathematics, Life Sciences, Economics or other relevant scientific subject
• Bachelor’s degree and 10 to 14 years of Computer Science, Statistics, Mathematics, Life Sciences, Economics or other relevant scientific subject
• Diploma and 14 to 18 years of Computer Science, Statistics, Mathematics, Life Sciences, Economics or other relevant scientific subject
• At least eight (8) years of relevant statistical programming, systems engineering or application programming experience in a clinical development or life sciences setting
• Managerial experience directly managing people and/or leadership experience leading teams, projects, programs or directing the allocation of resources in a statistical programming team working with real-world healthcare data (RWD)
• Experience leading a statistical programming team within RWE
• RWE generation in pharmaceutical or related research industries, or statistical programming for clinical trials
• Training or experience using the Observational Medical Outcomes Partnership (OMOP) common data model
• Department or multi-team management
• Global collaboration
• Request fulfilment oversight, clarifying requirements, project tracking, issue resolution, expert resource
• Statistical programming: SAS and SQL required
• R and Python preferred
• Experience working with real-world healthcare data (RWD) such as healthcare claims (MarketScan, Optum Clinformatics, Medicare) and EHR databases (Optum EHR PanTher, Flatiron, CPRD, MDV)
• Excellent verbal and written communication skills in English
• Ability to have efficient exchanges with colleagues across geographical locations
• Agile project management
• Real-world data (RWD) including insurance claims databases, electronic medical records and patient registries
• OMOP common data model
• Drug development life cycle
• Statistics and basic epidemiology: Incidence and prevalence
• Scientific / technical excellence
• Oral and written communication, documentation skills
• Leadership
• Innovation
• Teamwork
• Problem solving
• Attention to detail

• Experience with R and Python
• Preferably working within RWE generation
• Training or experience using the Observational Medical Outcomes Partnership (OMOP) common data model

Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards