Lead and deliver the translation of complex biological and clinical questions into actionable analysis plans.
Architect and implement robust data pipelines that integrate large-scale genomic, phenotypic, laboratory, and real-world clinical datasets.
Conduct repeatable data analysis and modeling with a high degree of scientific and statistical rigor, for complex tasks such as understanding patient trajectories, elucidating variant effect, and identifying genotype-phenotype associations.
Write clean, maintainable, and well-documented code following best practices for version control, testing, and scalability.
Prepare technical reports, peer-reviewed publications, and conference presentations to share research outcomes with internal stakeholders and the broader scientific community.
Collaborate closely with both internal and external stakeholders to drive impactful research and development initiatives.
Ensure high standards of data privacy, security, and compliance are maintained in all projects.

Requirements

Masters degree, or equivalent industry experience in Computer Science, Statistics, Data Science, Computational Biology, or a related field.
5+ years of hands-on experience in data science and statistical methods, as applied to large biomedical datasets.
Experience working within a collaborative technical team with strong software engineering practices.
Proficiency in modern programming languages (Python and SQL), shell scripting, and version control (Git).
Experience with data management, ETL, and business intelligence tools.
Excellent communication skills for presenting research findings to diverse audiences.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

data analysisstatistical methodsprogramming languagesPythonSQLshell scriptingversion controlETLbusiness intelligence

communicationcollaborationpresentation skills

Masters degree