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Company Description
Intrepid Biostats Insights is a biostatistics and clinical research support organization providing statistical programming and research solutions to academic institutions, healthcare professionals, pharmaceutical companies, biotechnology organizations, and research teams worldwide. The organization specializes in clinical research, epidemiology, public health, and biomedical data analysis, supporting projects from study design and statistical analysis to reporting and scientific publication.
The team provides end-to-end biostatistical support including statistical programming, clinical data analysis, sample size calculation, statistical modeling, data visualization, results interpretation, and preparation of research and regulatory documentation. Intrepid Biostats Insights follows ethical research practices, data confidentiality standards, and internationally accepted statistical methodologies to deliver high-quality, reproducible, and regulatory-compliant research solutions.
Role Description
The R Programmer (Biostatistics/Clinical Research) will work full-time on-site in Chennai, supporting clinical research and biostatistical projects through statistical programming, data management, and analytical reporting. The role involves developing, validating, and maintaining R-based programs for clinical trial data analysis, epidemiological studies, and healthcare research projects.
The R Programmer will collaborate with biostatisticians, clinical data managers, epidemiologists, and researchers to develop analysis datasets, perform statistical programming activities, and generate accurate outputs required for clinical study reports, manuscripts, research reports, and scientific presentations.
Key responsibilities include programming in R for data cleaning, transformation, statistical analysis, table/listing/figure (TLF) generation, exploratory data analysis, and automated reporting. The programmer will support the implementation of statistical analysis plans (SAPs), validate programming outputs, perform quality checks, document analytical processes, and ensure reproducibility and traceability of statistical deliverables.
The role also involves developing reusable R functions, optimizing analytical workflows, supporting automation initiatives, and contributing to the development of programming standards aligned with clinical research and CRO practices.
Qualifications
- Strong proficiency in R programming with experience in statistical programming and clinical research data analysis.
- Understanding of biostatistical concepts and clinical research methodologies, including clinical trial design, observational studies, epidemiological analysis, and healthcare research.
- Experience in programming statistical analyses using R for clinical and biomedical datasets.
- Knowledge of generating Tables, Listings, and Figures (TLFs) for clinical research reports and publications.
- Familiarity with statistical methods including descriptive analysis, hypothesis testing, ANOVA, regression models, logistic regression, survival analysis, longitudinal analysis, and mixed-effect models.
- Experience with R packages such as tidyverse, dplyr, ggplot2, data.table, survival, lme4, nlme, gt, flextable, officer, and R Markdown/Quarto.
- Knowledge of clinical trial data standards such as CDISC SDTM/ADaM, analysis datasets, and regulatory documentation is an added advantage.
- Ability to perform data validation, quality checks, programming review, and troubleshoot analytical issues.
- Familiarity with other statistical programming languages such as SAS, Python, or SQL is beneficial.
- Understanding of Good Clinical Practice (GCP), research ethics, data privacy, and regulatory compliance requirements.
- Experience working with clinical databases, electronic health records, real-world evidence data, or public health datasets is preferred.
- Bachelor's or Master's degree in Biostatistics, Statistics, Data Science, Bioinformatics, Public Health, Computer Science, or related disciplines.
- Strong attention to detail, analytical thinking, documentation skills, and ability to work effectively in a multidisciplinary CRO environment.
Preferred Skills
- Prior experience in CRO, pharmaceutical, biotechnology, healthcare analytics, or clinical research environments.
- Exposure to clinical study workflows, Statistical Analysis Plans (SAPs), and clinical study reports (CSR).
- Ability to translate statistical requirements into efficient and validated programming solutions.
- Commitment to producing high-quality, accurate, and audit-ready statistical programming deliverables.
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