Snr Scientist, Bioinformatics

Work Schedule: Standard (Mon-Fri)
Environmental Conditions: R&D Office

Position Summary

The Snr Scientist Bioinformatics will contribute to the design, development, and maintenance of computational pipelines, algorithms, databases, and infrastructure supporting assay development and genomic analysis. This role focuses on building and updating automated workflows that implement algorithms for qPCR applications. The successful candidate will collaborate closely with bioinformatics scientists, software engineers, and molecular biologists to ensure seamless integration of computational methods with experimental workflows.

Primary Responsibilities

Develop, maintain, and optimize bioinformatics pipelines and workflow automation for large-scale assay development.
Build and support Python-based tools, C/C++ algorithms, and SQL databases used in assay design and data analysis.
Perform and optimize sequence data analysis workflows for variant detection, indel identification, and alignment using tools like ClustalW, BLAST, BWA, or comparable methods.
Collaborate with internal teams to align pipeline outputs with laboratory processes and data systems.
Maintain version-controlled repositories, documentation, and reproducibility across computational workflows.
Participate in the publication or productization of developed algorithms, pipelines, or tools.

Required Qualifications

PhD in Bioinformatics, Computational Biology, Computer Science, or a related field with 3+ years of relevant experience, orMS with 5+ years of relevant experience.
Proven experience in bioinformatics pipeline development and workflow automation using Python and Linux environments. Experience developing or maintaining bioinformatics tools or algorithms that have been published or released as software products.
Strong programming skills in C/C++ and scripting for algorithm optimization.
Hands-on experience with relational databases (PostgreSQL, MySQL, or equivalent) including schema design, query optimization, and data integration.
Demonstrated understanding of genomics data analysis, including sequence alignment, indel calling, and variant annotation.
Familiarity with biological databases (NCBI, COSMIC, UCSC Genome Browser, etc.).
Proficiency with statistical and data science libraries (NumPy, SciPy, Pandas, scikit-learn, etc.).
Excellent problem-solving and debugging skills with attention to scalability and reproducibility.
Ability to collaborate effectively in a multi-disciplinary, distributed work environment.
Background in assay development or computational biology applications.

Preferred Qualifications

Working knowledge of Nextflow, Snakemake, WDL, or similar workflow management systems.
Familiarity with containerization (Docker, Singularity) and CI/CD practices for pipeline deployment.
Implement and manage cloud-based infrastructure (AWS preferred) to support scalable and reproducible computational workflows.
Experience deploying and maintaining computational workflows on cloud infrastructure (AWS or similar).
Experience optimizing workflows for high-performance computing (HPC) or cloud-native architectures.

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Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.

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Snr Scientist, Bioinformatics