The Role
Designs and analyzes in vitro experiments for pharmaceutical and life sciences research. Applies statistical models, validates data, develops statistical analysis plans and technical reports, supports regulatory submissions, and collaborates with scientists and researchers. Uses SAS, R, JMP, or Python for analysis, visualization, and reporting while ensuring compliance with FDA, ICH, and GLP requirements.
Summary Generated by Built In
Job Summary
We are seeking a skilled In Vitro Statistician with 4+ years of experience to support our research and development teams in statistical analysis of in vitro studies. The ideal candidate will be responsible for designing experiments, analyzing data, and providing statistical insights to support decision-making in pharmaceutical, biotechnology, or life sciences research.
Key Responsibilities:
- Design, develop, and analyze in vitro study experiments, ensuring statistical rigor and accuracy.
- Apply appropriate statistical models and methodologies for data interpretation.
- Work closely with scientists, biologists, and researchers to provide statistical guidance in study design and result evaluation.
- Utilize statistical software (e.g., SAS, R, JMP, or Python) to conduct data analysis, visualization, and reporting.
- Validate and verify data integrity, ensuring compliance with regulatory guidelines (FDA, ICH, GLP).
- Develop and review statistical analysis plans (SAPs), study protocols, and technical reports.
- Support regulatory submissions by preparing statistical documentation and reports.
- Stay updated with the latest statistical methods and best practices in in vitro research.
Required Qualifications & Skills:
- Master’s or Ph.D. in Statistics, Biostatistics, Bioinformatics, or a related field.
- 2-7 years of experience in statistical analysis of in vitro studies, preferably in the pharmaceutical, biotechnology, or life sciences sector.
- Strong knowledge of experimental design, regression models, ANOVA, DOE, and multivariate analysis.
- Proficiency in statistical software (SAS, R, JMP, Python, or equivalent).
- Experience with data visualization, trend analysis, and predictive modeling.
- Understanding of regulatory requirements and compliance standards (FDA, ICH, GLP).
- Excellent communication skills to present findings to cross-functional teams.
- Strong problem-solving skills and attention to detail.
Preferred Qualifications:
- Experience in bioassays, pharmacokinetics, biomarker analysis, or toxicology studies.
- Familiarity with machine learning and AI-based statistical modeling.
- Knowledge of clinical and preclinical statistical applications.
Skills Required
- Master's or Ph.D. in Statistics, Biostatistics, Bioinformatics, or a related field
- 2-7 years of experience in statistical analysis of in vitro studies, preferably in pharmaceutical, biotechnology, or life sciences
- Knowledge of experimental design, regression models, ANOVA, DOE, and multivariate analysis
- Proficiency in SAS, R, JMP, Python, or equivalent statistical software
- Experience with data visualization, trend analysis, and predictive modeling
- Understanding of FDA, ICH, and GLP regulatory requirements and compliance standards
- Excellent communication skills for presenting findings to cross-functional teams
- Strong problem-solving skills and attention to detail
- Experience in bioassays, pharmacokinetics, biomarker analysis, or toxicology studies
- Familiarity with machine learning and AI-based statistical modeling
- Knowledge of clinical and preclinical statistical applications
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The Company
What We Do
Vitely provides analytical testing and laboratory services for life sciences organizations while developing enabling technology. Its VitelyBio division offers microbiology and in‑vitro testing and regulated lab processes; VitelyTech delivers software development, automation, and data‑management solutions to support R&D workflows, regulatory compliance, and data integrity for pharmaceutical and biotech clients. The company focuses on high-quality, compliant analytical services and integrated digital tools to accelerate discovery across regulated environments.
