Senior Bioinformatician

Origin Sciences; Cambridge; Hybrid; GBP 65,000 - 85,000; Full time

Job summary

A health technology company in Cambridge is looking for a Senior Bioinformatician to lead the end-to-end analysis of genomic data and collaborate closely with clinical teams. Ideal candidates will have a PhD and extensive experience with various NGS data types. This role requires strong proficiency in Python and Nextflow, along with a solid grounding in statistics and machine learning. You will work onsite three days a week.

Qualifications

• 3+ years working with NGS data including methylation, variant, and microbiome.
• Strong data modelling skills.
• Experience operating pipelines on cloud or HPC.

Responsibilities

• Design, build, and maintain pipelines for various analyses.
• Translate complex analyses into clear narratives and reports.
• Provide mentorship and technical guidance.

Skills

Python

Nextflow

Docker

Machine Learning

Bioinformatics

Education

PhD in a computational field

Tools

R

Linux

Git

Job description

Overview

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About Ellele Health

Ellele Health is a medical research company reimagining diagnostics in women's health. Building on innovative IP and technology from our parent company, Origin Sciences, we are developing a novel, speculum-free vaginal sampling device that produces a richer biospecimen to power next-generation gynecological diagnostics and studies.

Ellele Health is a wholly owned subsidiary of Origin Sciences.

The role - Senior Bioinformatician for Ellele Health

You'll lead end-to-end analysis across methylation, mutation, and microbiome data to discover biomarkers and insights in human genomics, cancer, wellness, and disease. You'll design production-grade Nextflow pipelines, integrate lab/clinical metadata, and partner closely with wet-lab, clinical, and product teams to translate findings into validated, decision-ready outputs.

Key responsibilities

• Pipeline engineering (Nextflow): Design, build, and maintain robust, containerised pipelines for methylome, variant, and microbiome analyses; implement CI/CD, provenance, and reproducibility at scale (Docker/Singularity, Git, cloud/HPC).
• Methylation analytics: Process bisulfite/enzymatic sequencing; perform QC, normalization, batch correction, DMR calling, and pathway/region enrichment; evaluate clinical associations and predictive performance.
• Variant analysis: Implement best-practice alignment and (somatic/germline) calling; filtering/annotation; mutational signatures; copy-number; build cohort-level models.
• Microbiome & metagenomics: Run shotgun workflows for taxonomic/functional profiling; contamination control; host-microbe integration; link microbial features with host genetics and clinical phenotypes.
• Multi-omics integration: Develop reproducible feature engineering and ML/biostatistics frameworks (cross-validation, calibration, confounding control) to derive clinically meaningful signatures.
• Data management & governance: Define schemas and metadata standards; ensure traceability from instrument output to results; partner with Lab/Clinical Ops on LIMS/EDC integrations and data quality.
• Collaboration & communication: Translate complex analyses into clear narratives, dashboards, and reports for scientists, clinicians, and leadership; contribute to study design and sample size/power discussions.
• Quality & documentation: Establish testing, monitoring, and QC gates; write methods/SOPs; support publications and regulatory-grade documentation where needed.
• Mentorship: Provide technical guidance and code review; help shape best practices across the informatics stack.

Requirements

• PhD (or equivalent experience) in a computational field (Bioinformatics, Computational Biology, Computer Science, Statistics, Engineering, or related).
• 3+ years working with NGS data, including at least two of: methylation, variant, microbiome; experience combining them is a plus.
• Advanced proficiency in Python and/or R, linux, Git, Nextflow, and containerisation (Docker/Singularity); strong data-modelling skills.
• Solid grounding in statistics/ML (regression, regularisation, cross-validation, survival/time-to-event, feature selection).
• Experience operating pipelines on cloud or HPC (job schedulers, object storage, workflow orchestration, observability).
• Track record of collaborative work with laboratory/clinical teams and of delivering clear, reproducible analyses.
• Must be able to work onsite in Cambridge, UK 3 days per week.

Nice to have

• Experience in women's health, gynaecological cancers, or biomarker work; familiarity with clinical study data flows (LIMS/EDC).
• Knowledge of data privacy/ethics for human genomics and clinical data (e.g., UK GDPR), and writing methods/SOPs for regulated contexts.
• Visualisation and dashboarding (e.g., Plotly, R Shiny, Looker/Power BI/Tableau).