Genomics Software Engineer

Job Title : Genomics Software Engineer

Must Have skills :

Programming languages (e.g. Python, R)

Any workflow language - such as WDL and NextFlow

Single-cell RNA

UNIX / Linux operating system

Biotech / Phrama experience is must

Responsibilities

• Support data life cycle management projects that enable the storage, organization, dissemination, and analytics of data in alignment with the scientific objectives of the scientific functional groups.
• Understand the problems the scientists need to solve, and work to find the best solutions to those problems. Work effectively with geographically diverse engineering teams and scientific collaborators, ensuring clear and timely communication among all parties.
• Conduct generic image-based and spatial profiling data processing and primary to tertiary analysis and write up process documentation.
• Ensure delivery of relevant informatics solutions as workflows in WDL (Workflow Description Language), software packages in Python, and demos in Jupiter notebook.

Requirements

Hands-on experience wrangling, analyzing and visualizing biomedical data. Although not a requirement, additional consideration is given to candidates with experience working with single-cell RNA-seq and or spatial omics experiments.

e.g. 10x Visium, nanoString CosMx, 10x Xenium, etc.).

• Enthusiastic about working in a scientific environment, especially one focused on drug discovery and development.
• Have a flexible learning mindset and be able to work in a fluid and dynamic environment.
• Experience in software development using at least one of the mainstream programming languages (e.g. Python, R, C C++, etc.

Although not a requirement, additional consideration is given to candidates with experience with Python.

• Experience in workflow languages such as WDL and NextFlow.
• UNIX Linux operating system in the context of a scientific environment, especially one that is related to drug development.
• Self-motivated and enthusiastic about programming and software tool development.
• Demonstrated adherence to best practices in software engineering, particularly usability, version control, testing, and appropriate use of abstraction.
• Demonstrated ability to effectively communicate about complex bioinformatics problems to peers, users and leadership.

The interview process would include :

• 1-30min screen
• 2-3 30min interviews
• Possibly a code challenge

Additional information, such as the candidate's profile, and or a GitHub link are also useful.