About the job
Senior Bioinformatics Engineer
Join LatchBio, where we are pioneering AI agents that empower over 4,000 scientists in analyzing and interpreting data from cutting-edge spatial and multi-omic tools in the biotechnology sector.
We are looking for a highly skilled Senior Bioinformatics Engineer with a robust computational background—ideally, your expertise lies in computer science, mathematics, or statistics, complemented by a strong grasp of biological concepts. In this pivotal role, you will not only perform complex analyses but also establish quality benchmarks for your peers: reviewing analytical processes, identifying errors, and ensuring that all outputs are scientifically sound and defensible.
Your Responsibilities
Lead comprehensive biological data analyses across various projects, guiding data from raw platform outputs through QC, dimensionality reduction, cell typing, and differential expression to robust biological claims.
Oversee and evaluate the work of fellow bioinformatics engineers, ensuring analytical integrity and that all documentation meets gold-standard quality.
Develop reproducible workflows and maintain clear decision logs detailing filtering processes and rationale, changes in conclusions, and criteria for falsifying claims.
Design and implement computational tools or packages that enhance analysis efficiency within the team.
Essential Qualifications
A solid understanding of algorithms for high-dimensional data analysis (e.g., PCA, UMAP, neighborhood graphs, spectral methods) and the ability to discern their appropriate applications.
Proficient in statistical inference concepts: hypothesis testing, confidence intervals, estimators, and corrections for multiple testing.
Demonstrated experience in publishing or deploying computational tools or packages utilized by external users (open-source libraries, internal platforms, or production pipelines).
Successfully analyzed 3 or more datasets from raw data to actionable insights, suitable for publications or impactful industry experiments.
Knowledge of the landscape of computational biology tools for prevalent analysis tasks (e.g., clustering, cell typing, differential expression, enrichment).
Preferred Experience
Experience with comprehensive spatial transcriptomics analysis for technologies such as Seeker, Trekker (Slide-seq), MERFISH, DBiT-seq, Xenium, Visium, Stereo-seq, GeoMx, CosMx, or similar assays.
Advanced spatial reasoning skills beyond standard clustering, including neighborhood and adjacency enrichment, spatial gradients and niches, spatial differential expression, and spatial autocorrelation.

