Bioinformatics Scientist

We are seeking a highly motivated and skilled Bioinformatics Scientist to join our team. In this role, you will lead and contribute to the design, development, and execution of bioinformatics analyses to support [genomic research, drug discovery, precision medicine, or other biological innovations]. You will work with high-throughput biological data, develop computational pipelines, and help interpret complex datasets to generate meaningful scientific insights.

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Key Responsibilities:

• Analyze large-scale biological datasets, including next-generation sequencing (NGS), transcriptomics, epigenomics, and proteomics.

• Develop and maintain robust, scalable computational pipelines for data preprocessing, alignment, annotation, and statistical analysis.

• Collaborate with molecular biologists, clinicians, and data scientists to support interdisciplinary research and product development.

• Interpret and visualize biological data to identify patterns, biomarkers, or novel mechanisms relevant to human health and disease.

• Maintain accurate and well-documented code, protocols, and analysis reports to ensure reproducibility.

• Evaluate and integrate new bioinformatics tools, algorithms, and public datasets into research workflows.

• Present research findings to internal teams and contribute to scientific publications, presentations, and grant proposals.

Qualifications:

• Ph.D. or Masters degree in Bioinformatics, Computational Biology, Genomics, or a related field.

• [25+] years of hands-on experience in bioinformatics or computational biology.

• Strong programming and scripting skills (e.g., Python, R, Bash).

• Experience with NGS technologies and tools (e.g., BWA, STAR, GATK, DESeq2, SAMtools, BEDTools).

• Familiarity with biological databases (e.g., Ensembl, NCBI, UCSC Genome Browser).

• Solid foundation in molecular biology, genetics, and statistics.

• Strong communication skills and ability to work in a collaborative, fast-paced environment.

Preferred Skills:

• Experience with cloud computing environments (AWS, GCP) and workflow management tools (Nextflow, Snakemake).

• Familiarity with version control (e.g., Git) and containerization (Docker, Singularity).

• Background in a specific therapeutic area (e.g., oncology, rare disease, infectious disease).

• Experience with single-cell data analysis, multi-omics integration, or clinical genomics.