Developing and validating R programs for statistical analysis and reporting of clinical trial data.
Leading more than one Statistical Programming team to create, validate and generate statistical outputs, including listings, tables, figures, and CDISC-compliant SDTM and ADaM datasets.
Collaborating with biostatisticians to define analysis plans and statistical methods to be applied to clinical data.
Performing quality control and validation of statistical outputs, ensuring accuracy, consistency, and regulatory compliance.
Assisting in the preparation of statistical reports, presentations, and publications to support regulatory submissions and clinical study reporting.
Requirements
Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Life Sciences, or a related quantitative field.
Provide hands‑on statistical programming support for clinical studies, developing and validating analysis datasets, tables, listings, figures, and graphs for regulatory submissions and internal presentations.
Compensation
Bill Rate is *** On Site or Remote Provide hands‐on statistical programming support for clinical studies, including development and validation of analysis datasets and statistical outputs, in accordance with regulatory and company standards.
Responsibilities
Develop complex analysis datasets, specifications, and summary outputs
Create, modify, and maintain SAS programs
Perform independent program review and validation
Support ad hoc and planned analyses
Partner with Clinical Data Management and Biostatistics
Requirements
Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related field
Master’s degree (or equivalent) in a related field
Nice to have: R
Nice to have: Python
Nice to have: Experience with regulatory submissions
Lead biostatistician overseeing complex clinical trial studies, managing statistical strategy, design, analysis, and regulatory submissions.
Responsibilities
Serve as lead statistician on complex, key client studies
Act as point-of-contact ensuring cohesive communication with sponsors and internal teams
Lead project-level statistical strategy from protocol/SAP planning through reporting
Develop sample size estimation, modeling approaches, adaptive or Bayesian frameworks, and innovative trial designs
Provide senior oversight for statistical deliverables including SAPs, randomization specifications, and statistical contributions to CSRs, publications, and regulatory documents
Requirements
Advanced degree (MS or PhD) in statistics or closely related field
Serve as lead statistician on complex, key client studies, acting as point-of-contact, and leading project-level statistical strategy from protocol/SAP planning through reporting.
Responsibilities
Serve as lead statistician on complex, key client studies, ensuring cohesive communication with sponsors and internal teams
Communicate complex quantitative concepts clearly to non-statistical stakeholders
Develops sample size estimation, modeling approaches, adaptive or Bayesian frameworks, and innovative trial designs
Develops or provides senior oversight for statistical deliverables, including statistical selection of protocols, statistical Analysis Plans (SAPs), randomization specifications, and Statistical contributions to CSRs
Identify risks related to study design, sample size, or analysis approaches and proactively propose mitigation strategies
Lead statistician overseeing complex clinical trial studies, managing statistical strategy, and ensuring regulatory compliance.
Responsibilities
Serve as lead statistician on complex, key client studies
Act as point-of-contact ensuring cohesive communication with sponsors and internal teams
Lead project-level statistical strategy from protocol/SAP planning through reporting
Develop sample size estimation, modeling approaches, adaptive or Bayesian frameworks, and innovative trial designs
Provide senior oversight for statistical deliverables including SAPs, randomization specifications, and statistical contributions to CSRs, publications, and regulatory documents
Requirements
Advanced degree (MS or PhD) in statistics or closely related field
Lead biostatistician overseeing complex clinical trial studies, managing statistical strategy, design, analysis, and regulatory submissions.
Responsibilities
Serve as lead statistician on complex key client studies
Act as point-of-contact ensuring cohesive communication with sponsors and internal teams
Lead project-level statistical strategy from protocol/SAP planning through reporting
Develop sample size estimation, modeling approaches, adaptive or Bayesian frameworks, and innovative trial designs
Provide senior oversight for statistical deliverables including SAPs, randomization specifications, and statistical contributions to CSRs, publications, and regulatory documents
Requirements
Advanced degree (MS or PhD) in statistics or closely related field
A senior-level leadership position focused on overseeing the end-to-end statistical programming lifecycle, combining technical oversight, project management, and cross-functional collaboration.
Compensation
The expected base salary for this position is: $153616.00 to $199501.00. We are committed to compensating employees equitably based on several factors including experience, education, licensure/certifications, skill level, location of the position, and availability of similar talent in a competitive market. Subject to eligibility and applicable plan terms, compensation includes base salary, annual discretionary bonus, long term incentive, 401(K) plan with employer contribution, health care and other insurance benefits (for employee and family), paid holidays, vacation, and sick days.
Responsibilities
Lead or Co-ordinate statistical programming activities of all programmers either internally or externally assigned to the study/project work
mentor other programmers in functional expertise and processes
Make statistical programming decisions/recommendations at study or project level
Comply with company, department and industry standards (e.g. CDISC) and processes
responsible for quality control and audit readiness of all assigned statistical programming deliverables as well as accuracy and reliability of statistical analysis results
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