Senior Data Scientist, Single-Cell Multiomics ML

Relation; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Relation in London is seeking a Senior Data Scientist to build generative and predictive models of cellular behaviour from single-cell multiomics data. You will develop pipelines and analyse large-scale RNA+ATAC data, collaborating closely with wet labs and ML modellers.

The role focuses on advanced data analysis, model evaluation, and cross-disciplinary impact. You will contribute to publications and work in a matrixed, interdisciplinary environment with state-of-the-art datasets and computing

Qualifications

• PhD (or equivalent) in computational biology, bioinformatics, or related field.
• Deep hands-on experience processing large-scale single-cell multiomics data (RNA+ATAC).
• Proficiency with single-cell analysis toolkits and workflow managers (Nextflow, Snakemake).
• Experience with arrayed CRISPR perturbation data and perturbation QC.

Responsibilities

• Process and QC paired single-cell RNA-seq and scATAC-seq data at scale across diverse contexts.
• Develop and maintain Nextflow/Snakemake pipelines for multimodal datasets.
• Integrate scRNA-seq and scATAC-seq with proteomics and imaging for multimodal training datasets.
• Collaborate with wet lab scientists to ensure analytical tractability of experiments and maximize data value.
• Contribute to evaluation frameworks and present findings to stakeholders.

Skills

Single-cell analysis

Python

Nextflow

Snakemake

MOI estimation

Data processing

High-performance computing

Communication skills

Education

PhD or equivalent in computational biology

Tools

STARsolo

Alevin-fry

Chromap

SnapATAC2

scverse ecosystem

Job description

Relation in London is seeking a Senior Data Scientist to build generative and predictive models of cellular behaviour from single-cell multiomics data. You will develop pipelines and analyse large-scale RNA+ATAC data, collaborating closely with wet labs and ML modellers.

The role focuses on advanced data analysis, model evaluation, and cross-disciplinary impact. You will contribute to publications and work in a matrixed, interdisciplinary environment with state-of-the-art datasets and computing