Python Scientific Informatics Engineer
Our client, a leading global pharmaceutical company, is seeking a highly skilled and motivated Bioinformatics Scientist to join their international research organization, driving innovation across multiple therapeutic areas. In this role, you will design, evaluate, and optimize computational methods for large-scale next-generation sequencing (NGS) analysis, contributing directly to discovery and development programs. You will build robust, production-grade bioinformatics workflows for high-performance computing (HPC) clusters and cloud environments, collaborating closely with biologists, data scientists, and domain experts across Oncology, Immunology, Infectious Diseases & Vaccines, Neuroscience, and Pharmacokinetics.
Responsibilities
- Develop, benchmark, and optimize computational methods to analyze diverse NGS datasets
- Build and maintain scalable, automated bioinformatics pipelines for HPC and cloud-based execution
- Partner with interdisciplinary scientific teams to translate research needs into reproducible analytical workflows
- Evaluate and implement new algorithms, tools, and computational strategies to enhance data processing capabilities
- Produce clear technical documentation, reports, and scientific deliverables
Requirements
- PhD with 1+ year of experience in bioinformatics, or MSc with 5+ years of relevant experience
- Hands-on experience in processing NGS datasets (WGS, WES, RNA-seq, ChIP-seq, ATAC-seq, single-cell, etc.)
- Practical experience with workflow/pipeline scripting languages (e.g., Nextflow)
- Strong understanding of computational methods for alignment, assembly, variant detection, enrichment, or related genomics applications
- Familiarity with common bioinformatics file formats (FASTA, FASTQ, BAM, VCF, etc.)
- Proficiency in Python, R, or C++ within a Unix/Linux environment
- Experience with high-performance computing clusters and cloud computing platforms
- Ability to independently troubleshoot using documentation, GitHub, and online resources
- Proven scientific publication record
- Strong collaboration, communication, and interpersonal skills
- Excellent written and spoken English (B2 level or higher)
Nice to have
- Experience with containerization technologies, such as Docker or Singularity
- Experience in applying or optimizing machine learning tools within a bioinformatics context
