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Data Scientist – Research | Computational Genomics
📍 London, King’s Cross | Hybrid – Tuesday to Thursday onsite
⏳ 6-month contract
💷 £55.77 per hour PAYE + holiday pay
We are looking for a Data Scientist – Research to join a leading AI research organisation, working within a genomics team developing state-of-the-art deep learning models for scientific research. This is a highly specialised role sitting at the intersection of computational genomics, bioinformatics, and machine learning.
The primary focus will be preparing large-scale genomic datasets for deep learning model training. You will work closely with scientists and engineers to ingest new datasets, process and standardise genomic data, assess data quality, and ensure datasets are structured appropriately for downstream model training.
This would suit a computational biologist, bioinformatician, or genomics-focused Data Scientist who combines strong hands-on genomic data experience with Python and understands how high-quality biological datasets are prepared for machine learning.
What you'll be doing
- Ingesting, processing, formatting, and quality-controlling large-scale genomic datasets
- Preparing genomic data for use in deep learning model training
- Building and improving scalable bioinformatics and data-processing pipelines
- Assessing new datasets for quality and suitability before incorporation into modelling workflows
- Working with genomic data relating to gene regulation and chromatin biology
- Working extensively in Python and relevant bioinformatics/data-processing libraries
- Handling common genomic formats including FASTQ, BAM, BED, and bigWig
- Working closely with scientists and engineers developing and training genomics models
- Iterating on datasets and pipelines as research and modelling requirements evolve
- Processing biological data at significant computational scale
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What we're looking for
- Proven experience preparing data for machine learning/deep learning models
- Strong hands-on experience working with genomic data
- Understanding of functional genomics, particularly gene regulation and/or chromatin biology
- Strong Python skills, including Pandas, NumPy, and relevant bioinformatics libraries
- Experience developing or working with large-scale bioinformatics/data-processing pipelines
- Familiarity with genomic formats such as FASTQ, BAM, BED, and bigWig
- Experience with bioinformatics tooling such as samtools, bedtools, or equivalent
- Ability to understand the biological context of the genomic data being processed
- Experience working with large datasets and/or large-scale compute environments
- Ability to work independently while collaborating closely with scientists and engineers
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Particularly useful experience
- Single-cell genomics
- Comparative or multi-species genomics
- Genomic foundation models or other deep learning models
- Automated or agentic biological data-processing workflows
- Cloud or HPC environments
- Large-scale scientific research or AI/ML environments
- Familiarity with Google infrastructure is beneficial but not required
Who could be a good fit?
We're open to candidates from either academic or industry backgrounds. A degree in bioinformatics, computational biology, or a related discipline would be beneficial, although candidates from broader natural sciences backgrounds with substantial hands-on bioinformatics experience are equally relevant.
We're also open on seniority. You could be an experienced bioinformatician with deep functional genomics expertise, or earlier in your career with particularly strong technical experience across modern genomics and machine learning.
What's most important is that you understand genomic data, can work with it confidently in Python, and have experience preparing high-quality datasets for machine learning.
The team is highly collaborative and is looking for someone who can take ownership, work independently, and get up to speed quickly within a fast-moving research environment.
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