We are looking for a highly motivated  Senior Bioinformatics Data Scientist to join our team!

As a Senior Bioinformatics Data Scientist, you will develop the next generation of analysis methods for our unique genomic datasets and will be a central driver of our scientific discovery, working at the intersection of biology, computer science, and machine learning. You will be creating the novel computational strategies and scalable pipelines that unlock the insights hidden within our data.

How You’ll Contribute

• Architect & Implement: Design, build, and optimize robust bioinformatics pipelines for analyzing large-scale Next-Generation Sequencing (NGS) datasets efficiently and cost-effectively in a cloud/HPC environment
• Innovate & Analyze: Develop novel algorithms and adapt cutting-edge methods to extract meaningful biological insights from complex, high-throughput data
• Collaborate & Influence: Partner cross-functionally with our lab scientists, data scientists, and clinical partners to understand their needs, provide analytical expertise, and help shape the design of our scientific platform
• Drive Scientific Rigor: Apply sophisticated statistical analysis, machine learning models, and probabilistic modeling to ensure the accuracy and impact of our findings

Qualifications, Skills, Knowledge & Abilities

• Degree in Computational Biology, Bioinformatics, Computer Science, or a related discipline
• MS degree with 5+ years or PhD degree with 3+ years of relevant industry or academic experience in a hands-on bioinformatics role
• Demonstrated experience analyzing and interpreting large-scale NGS datasets (e.g., WGS, WES, RNA-seq, SingleCell, cfDNA)
• Expert proficiency in Python for complex data analysis
• A strong foundation in statistics, algorithm design, and machine learning
• Proficiency with software development best practices (e.g., version control with Git, containerization with Docker, unit testing)
• A track record of applying machine learning frameworks (e.g., PyTorch, scikit-learn) to biological problems
• Deep expertise in a specific area of genomics, such as somatic variant calling, structural variation, or single-cell analysis
• Hands-on experience deploying and managing bioinformatics workflows in a cloud environment (AWS/GCP) using tools like WDL, Nextflow or Snakemake

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