Bioinformatics Scientist - Genomics Analysis

Placements24; LegKraal Gate; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Remote work

Home office allowance

Virtual training access

Job summary

Placements24 represents a forward-thinking biotechnology company recruiting a Bioinformatics Scientist for a remote R&D team. You will analyze large-scale genomic datasets to identify genetic variations, biomarkers, and therapeutic targets.

Collaborating with biologists, computational scientists and clinicians, you will build pipelines, apply statistical and ML methods, and communicate findings through reports and presentations.

Qualifications

• PhD or Master's in a quantitative field with genomic data experience.
• Experience in variant calling, annotation, and association studies.
• Proficiency in Python or R and bioinformatics tools.

Responsibilities

• Analyze high-throughput sequencing data (WGS, WES, RNA-Seq) to identify variants.
• Develop and refine bioinformatics pipelines for genomic analysis.
• Collaborate with experimental teams to design genomic studies.
• Apply statistical genetics and machine learning to predict outcomes.
• Communicate results to technical and non-technical audiences via reports.
• Keep up-to-date with genomics tools and methods.

Skills

Python

R

Genomics data analysis

Cloud computing

Git

Education

PhD in Bioinformatics

MSc in related field

Tools

GATK

ANNOVAR

Ensembl

Job description

About the Role

Our client, a forward-thinking biotechnology company, is actively recruiting a Bioinformatics Scientist to join their innovative, fully remote R&D team. This role is essential for the analysis of large-scale genomic datasets, enabling the discovery of genetic variations, biomarkers, and therapeutic targets. You will collaborate virtually with a diverse team of biologists, computational scientists, and clinicians, applying cutting-edge computational and statistical methodologies to complex biological problems. This is an exceptional opportunity for a skilled bioinformatician to make a significant impact on genomic research and drug discovery from a remote location, supported by a company culture that values collaboration, innovation, and work-life balance.

Key Responsibilities

• Analyze and interpret high-throughput sequencing data (e.g., WGS, WES, RNA-Seq) to identify genetic variants and biological insights.
• Develop, implement, and refine bioinformatics pipelines for genomic data processing and analysis.
• Collaborate with experimental teams to design genomic studies and interpret findings in the context of biological questions.
• Utilize statistical and machine learning approaches to uncover patterns and predict outcomes from genomic data.
• Communicate complex bioinformatics results effectively to both technical and non-technical audiences through reports and presentations.
• Stay abreast of the latest advancements in genomics, bioinformatics tools, and computational methods.

Requirements

• Ph.D. or Master's degree in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field.
• Proven experience in analyzing large-scale genomic data, including variant calling, annotation, and association studies.
• Proficiency in programming languages such as Python or R, and experience with bioinformatics tools and databases (e.g., GATK, ANNOVAR, Ensembl).
• Strong understanding of statistical genetics, population genetics, and machine learning concepts.
• Experience with cloud computing environments (AWS, GCP, Azure) and version control systems (Git) is preferred.

Benefits

• Highly competitive salary and a comprehensive benefits package.
• Generous home office allowance and support for remote work infrastructure.
• Significant opportunities for professional growth, including access to virtual training and conferences.
• A flexible and dynamic remote-first work environment fostering innovation and autonomy.
• The chance to contribute to groundbreaking discoveries in genomics and personalized medicine from Mahikeng (remote work location).