Description

You will develop high-performance systems for the interactive analysis of large-scale cellular and tissue profiling data.

Responsibilities

• Build performant systems capable of querying data from distributed sources to feed visualization interfaces.
• Solve scientific software engineering challenges related to spatial transcriptomics and data analysis.
• Collaborate with computational scientists, business analysts, and engineering teams to conceptualize technical requirements.
• Contribute to the scientific community through open-source software development.
• Support software development efforts by working with local and offshore engineering teams.

Required Skills

• 5+ years of experience in Python, including package development and designing high-performance systems.
• 3+ years of experience developing Python tools for High Performing Computers and cloud solutions.
• Expertise with performant file formats such as HDF5, Zarr, or TileDB.
• Experience deploying performant software in AWS environments to establish APIs and data services.
• Proficiency with scientific computing packages including SciPy, NumPy, and Pandas.
• Strong adherence to software engineering best practices, including version control, testing, usability, and abstraction.
• BS or higher in Bioinformatics, Computer Science, or a related field.

Preferred Skills

• Familiarity with single-cell RNA-seq, CITE-Seq, or single-cell ATAC-seq data analysis.
• Experience with formal build, release, deploy, and continuous integration frameworks.
• Biological domain knowledge in single-cell genomics.

Key Skills

Education

Any Gradute