Manager, Translational Genetics (Therapeutic Area Genetics)

Role Summary

Role title: Manager, Translational Genetics (Therapeutic Area Genetics). Aims to develop and maintain applications and libraries to analyze and interpret large-scale genomic data, enabling scientists to efficiently interact with analysis results from massive human genetics studies. Collaborate with multidisciplinary teams to translate findings into new biological insights.

Responsibilities

• Architect robust, reusable software that abstracts complex genetic analyses into scalable tools; transform one-off analyses into production-grade packages used across the team.
• Mine massive sequencing datasets to uncover biological insights that drive drug development.
• Optimize algorithms for performance at scale; refactor legacy codebases and implement modern software engineering practices (version control, CI/CD, containerization) in a scientific context.
• Debug issues, write comprehensive documentation, and provide technical mentorship to users of your tools.
• Collaborate with geneticists, clinicians, and bioinformaticians to understand analytical needs and translate them into software solutions; co-develop novel analysis strategies.
• Integrate cutting-edge methods in statistical genetics; use current GWAS and post-GWAS methods, integrate diverse data types, and generate testable hypotheses about human disease.

Qualifications

• Required: Masters or PhD in Bioinformatics or Statistical Genetics with a strong computational component, or a degree in Computer Science, Applied Mathematics, Physics, or other quantitative field with specialization in genetics.
• Required: Hands-on experience with statistical genetics, GWAS and post-GWAS.
• Required: Strong expertise in writing efficient scientific code in R, Python, or other languages.
• Preferred: Development of scientific packages and/or web applications.
• Required: Experience developing and deploying in a cloud infrastructure (e.g., AWS, GCP, DNAnexus) using CI/CD and software containerization (Docker).
• Required: Familiarity with standard bioinformatics tools (e.g., PLINK2, HTSlib, tabix) and data formats (e.g., VCF, BED, BGEN).
• Required: Experience working with Linux/UNIX command line and SQL databases.

Skills

• Quantitative aptitude with a focus on clean, well-structured code.
• Knowledge of polygenic scores, LD, GWAS and post-GWAS; ability to disentangle loci without primer guidance.
• Ability to refactor duplicated logic into well-designed, composable functions.
• Team collaboration to translate analytical needs into software solutions and to push the field forward.

Education

• Master’s or PhD in Bioinformatics or Statistical Genetics, or equivalent in Computer Science, Applied Mathematics, Physics, or other quantitative field with genetics specialization.

Additional Requirements

• Hands-on experience with cloud infrastructure, CI/CD, and containerization (Docker).
• Experience with Linux/UNIX command line and SQL databases.