Senior Biostatistician

Placements24; Komani; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Bonuses

Health insurance

Remote work

Paid time off

Professional development

Data-driven culture

Job summary

Placements24 is seeking a Senior Biostatistician to join our client's R&D team in a remote capacity. You will lead the design, analysis, and interpretation of clinical trial data, develop statistical analysis plans, and support regulatory submissions.

The ideal candidate holds a Master’s or PhD in Biostatistics and has 7+ years in the field. Expertise in SAS or R and strong communication skills are essential to collaborate with cross-functional teams and drive data-driven decisions in

Qualifications

• Master's or Ph.D. in Biostatistics, Statistics, or related quantitative field (required).
• Minimum of 7 years of biostatistics experience in pharma/biotech (required).
• Proficiency in SAS and/or R for analyses (required).
• Strong understanding of clinical trial design and data analysis techniques (required).
• Experience with regulatory submissions (INDs/NDAs) is desirable.

Responsibilities

• Develop SAPs for clinical trials in line with protocols and regulatory requirements.
• Perform complex statistical analyses using SAS, R, or other software.
• Design clinical trials, including sample size calculations and randomization schemes.
• Interpret results and contribute to CSRs, manuscripts, and submissions.
• Provide statistical consultancy to clinical teams and researchers.

Skills

Communication skills

Analytical thinking

Remote teamwork

Education

Master's or PhD in Biostatistics

Tools

SAS

R

Job description

About the Role

Our client is seeking a highly skilled and experienced Senior Biostatistician to join their research and development team, working remotely. This role is vital for the design, analysis, and interpretation of clinical trial data, ensuring the statistical validity and integrity of research findings. You will play a key part in developing statistical analysis plans, performing complex statistical modeling, and preparing reports for regulatory submissions. The ideal candidate will possess a strong theoretical and applied knowledge of biostatistics, proficiency in statistical software, and the ability to collaborate effectively with cross-functional teams, contributing to the successful execution and reporting of clinical studies that drive pharmaceutical innovation and patient benefit.

Key Responsibilities

• Develop statistical analysis plans (SAPs) for clinical trials, ensuring alignment with study protocols and regulatory requirements.
• Perform complex statistical analyses using SAS, R, or other statistical software packages.
• Design clinical trials, including sample size calculations and randomization schemes.
• Interpret statistical results and contribute to the preparation of clinical study reports (CSRs), manuscripts, and regulatory submissions.
• Provide statistical expertise and consultation to clinical development teams and researchers.
• Stay current with advancements in statistical methodologies and regulatory guidelines.

Requirements

• Master's or Ph.D. degree in Biostatistics, Statistics, or a related quantitative field.
• Minimum of 7 years of experience in biostatistics within the pharmaceutical or biotechnology industry.
• Proficiency in statistical programming using SAS and/or R.
• Strong understanding of clinical trial design, statistical modeling, and data analysis techniques.
• Experience with regulatory submissions (e.g., INDs, NDAs) is highly desirable.
• Excellent analytical, problem-solving, and communication skills, with the ability to work effectively in a remote team environment.

Benefits

• Highly competitive annual salary and performance-related bonuses.
• Comprehensive health, dental, and vision insurance.
• Flexible remote work opportunities.
• Generous paid time off and holidays.
• Opportunities for professional development, including attending conferences and workshops.
• A stimulating and collaborative environment focused on data-driven decision-making and scientific rigor.