Senior Statistical Programmer, R, RShiny
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Job Description
Lead statistical programming for Syneos Health’s clinical drug development services using R/RShiny. Developing CDISC-compliant clinical trial outputs and mentoring programming teams.
Responsibilities:
- Use R/RShiny or other software to develop custom programming code for summary tables, data listings, graphs and derived datasets
- Ensure outputs meet quality standards and project requirements
- Perform validation programming and resolve discrepancies with Programmers, Biostatisticians and project team members
- Keep project team members informed of programming progress and issues
- Follow applicable SOPs, WIs and regulatory guidelines such as ICH
- Maintain complete, current project documentation, testing and quality-control records
- Manage schedules and priorities across multiple projects
- Develop specifications for datasets and outputs of any complexity
- Anticipate and address programming issues and define variables for peer review and sponsor/requestor acceptance
- Prepare for and conduct internal meetings, distribute information and minutes, and follow action items through completion
- Assist with projects and initiatives as needed
- Establish time estimates and complete study programming activities within allotted timeframes
- Act as lead statistical programmer and direct other programming personnel
- Review Statistical Analysis Plans, mock shells, programming specifications, annotated CRFs and SAS database designs
- Participate in sponsor, kickoff and bid defense meetings as statistical programming representative
- Mentor programming personnel through training, work review, feedback and guidance
- Transfer deliverables
- Perform other assigned work-related duties
Requirements:
- Advanced degree in Statistics, Computer Science, or a related field
- Extensive experience in statistical programming in a clinical or pharmaceutical setting
- Experience with CDISC programming (SDTM, ADaM)
- Experience with clinical trials and biomarker analyses
- Proficiency in R and RShiny
- Strong understanding of statistical methods and data analysis techniques
- Excellent problem-solving and analytical skills
- Ability to work independently and as part of a team
- Strong communication and interpersonal skills
- SAS Certified Advanced Programmer for SAS 9 or equivalent certification preferred
- Equivalent experience, skills, and/or education will also be considered
Benefits:
- Career development and progression
- Supportive and engaged line management
- Technical and therapeutic area training
- Peer recognition
- Total rewards program
- Inclusive culture
- Comprehensive resources including emerging technologies, data, science and knowledge sharing
- Opportunities for career paths and employment progression
- Minimal travel may be required
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