Junior Biostatistician

About the role

ClinSoft LLC is a biometrics and technology company providing end-to-end clinical study support to pharmaceutical and biotechnology organizations worldwide. It offers Clinical Research Services, Bioinformatics, Biostatistics and related healthcare technology services on international projects. The Junior Biostatistician is a full-time, on-site position in Yerevan, Armenia, supporting clinical trials and research studies through statistical analyses under the guidance of senior biostatisticians. The role suits recent graduates and early-career candidates with a background in statistics or a related quantitative field.

Key responsibilities

• Support statistical analyses, interpretation and reporting for clinical research projects
• Contribute to analysis datasets, including modeling, visualization and data processing
• Write and maintain clear, reproducible code in R or SAS
• Help review statistical analysis outputs for accuracy, consistency and quality
• Collaborate with biometrics, statistical programming, data management, medical writing and other project teams
• Support study activities in line with applicable standards and guidelines

Required profile

• Bachelor's or Master's degree in Biostatistics, Statistics, Mathematics, Data Science, Econometrics or a related quantitative field
• Solid grounding in probability and inference, hypothesis testing, regression and study design
• Working knowledge of English to read and work with technical documentation
• Exposure to statistical reporting, technical documentation or research data analysis
• A thesis, research project, code portfolio (e.g. GitHub) or similar work showing quantitative and programming ability
• Interest in clinical research, regulatory requirements and GCP; prior healthcare or pharma experience is an advantage

Required skills

• Working knowledge of at least one statistical programming language (R preferred)
• Ability to write clear, reproducible code and to learn new tools quickly
• Plus: regression, repeated-measures/mixed models, categorical data, survival analysis, simulation and data visualization