Senior Biostatistician, Biostatistics, R&D, Orion Corporation

Orion Pharma•Boston, MA

4d•Hybrid

About The Position

You will join a growing oncology-focused Data Sciences function and provide statistical support across Phase I–III oncology studies within our expanding portfolio. The Senior Biostatistician contributes to the design, analysis, interpretation, and reporting of oncology clinical trials across the portfolio. With a particular focus on biomarker, translational, and precision medicine analyses, the Senior Biostatistician collaborates closely with Clinical Development, Translational Medicine, Data Sciences, Statistical Programming, and external partners to deliver high-quality statistical solutions throughout the drug development lifecycle.

Requirements

PhD or MS in Statistics, Biostatistics, or related field.
MS with approximately 4–8 years, or PhD with 2–5 years, of relevant experience in clinical development, oncology preferred.
Strong understanding of statistical methods and their application in drug development.
Proficiency in SAS (required); working knowledge of R.
Demonstrated interest in applying AI-enabled approaches to improve statistical workflows, data analysis efficiency, visualization, and decision support.

Responsibilities

Contribute to the design and statistical sections of clinical trial protocols, including endpoint selection, sample size considerations, and randomization approaches.
Support analyses of predictive, prognostic, pharmacodynamic, and other biomarker data to inform development decisions and patient selection strategies.
Participate in the integration and interpretation of clinical and biomarker findings to generate actionable insights.
Plan, prepare, and execute statistical analyses according to SAPs.
Generate and review tables, listings, and figures (TLFs).
Ensure statistical deliverables adhere to CDISC standards (SDTM, ADaM).
Support clinical study reporting and regulatory documents.
Collaborate with clinical, data management, and programming teams throughout the study lifecycle.
Contribute to the evaluation and appropriate use of AI-assisted tools, automation, and advanced analytics approaches that enhance statistical efficiency and insight generation.