Senior Bioinformatics Analyst

Placements24; Randburg; Hybrid; ZAR 1,100,000 - 1,700,000; Full time

Benefits offered by this job

Bonuses

Health insurance

Retirement plan

Professional development

Hybrid work environment

High-performance computing resources

Job summary

Placements24 in Randburg is seeking a highly skilled Senior Bioinformatics Analyst to join our advanced research group on a hybrid basis. You will design and run analytical pipelines for genomic and transcriptomic data, and collaborate with researchers to interpret complex results.

You will mentor junior analysts, contribute to databases, and develop novel computational approaches using Python or R, with strong command-line experience.

Qualifications

• Master's or Ph.D. in Bioinformatics, Computer Science, Statistics, or related quantitative field.
• Minimum of 5 years hands-on experience as a Bioinformatics Analyst.
• Strong programming skills in Python or R, and proficiency with command-line interfaces.
• Experience with NGS data analysis (RNA-Seq, ChIP-Seq, variant calling).
• Excellent communication and interpersonal skills, with the ability to work in a hybrid Randburg setting.

Responsibilities

• Analyze large-scale genomic, transcriptomic, and proteomic datasets.
• Develop and implement custom scripts and algorithms for data processing and analysis.
• Collaborate with biologists and geneticists to define research questions and strategies.
• Interpret complex data and present findings clearly to diverse audiences.
• Contribute to developing and maintaining bioinformatics databases and resources.
• Mentor junior analysts and provide technical support to research teams.

Skills

Communication

Interpersonal skills

Education

Master's or PhD in Bioinformatics / CS / Statistics

Tools

Python

R

Command-line

Job description

About the Role

Our client is seeking a highly skilled Senior Bioinformatics Analyst to join their advanced research group, operating under a hybrid model in Randburg . This role is central to extracting meaningful biological insights from complex genomic and transcriptomic datasets. You will be responsible for designing and executing analytical pipelines, developing novel computational approaches, and collaborating with researchers to interpret results. This is an exceptional opportunity for an experienced analyst to contribute to groundbreaking studies, leverage cutting-edge technologies, and foster scientific discovery within a dynamic and supportive hybrid work environment.

Key Responsibilities

• Analyze large-scale genomic, transcriptomic, and proteomic datasets using state-of-the-art bioinformatics tools and pipelines.
• Develop and implement custom scripts and algorithms for data processing, quality control, and statistical analysis.
• Collaborate with biologists and geneticists to define research questions and design appropriate analytical strategies.
• Interpret complex biological data and present findings clearly to both technical and non-technical audiences.
• Contribute to the development and maintenance of bioinformatics databases and resources.
• Mentor junior analysts and provide technical support to research teams.

Requirements

• Master's or Ph.D. in Bioinformatics, Computer Science, Statistics, or a related quantitative field.
• Minimum of 5 years of hands-on experience as a Bioinformatics Analyst.
• Strong programming skills in Python or R, and proficiency with command-line interfaces.
• Experience with next-generation sequencing (NGS) data analysis (e.g., RNA-Seq, ChIP-Seq, variant calling).
• Familiarity with various bioinformatics databases and publicly available resources.
• Excellent communication and interpersonal skills, with the ability to work effectively in a hybrid setting in Randburg .

Benefits

• Competitive annual salary with performance-based bonuses.
• Comprehensive health, dental, and vision insurance coverage.
• Retirement savings plan.
• Opportunities for professional development, training, and conference attendance.
• Flexible hybrid work schedule balancing remote and in-office collaboration.
• A stimulating research environment with access to high-performance computing resources.