Immunology Data Scientist – Translational Research

Hyper Recruitment Solutions; Windlesham; On-site; GBP 65,000 - 90,000; Full time

Benefits offered by this job

Equal opportunities employer

Job summary

Hyper Recruitment Solutions Ltd in the UK seeks a Research Data Scientist - Immunology to join a leading biopharmaceutical company. The role focuses on generating, analysing and translating preclinical data to inform immunology therapies, with an initial base at the current site before a move to Windlesham, Surrey, mid-2027.

You will work with interdisciplinary teams on translational research, analyze large datasets (RNAseq, scRNAseq, proteomics), and manage external CROs while ensuring

Qualifications

• A Degree or higher level in a relevant field (Immunology, Systems Biology, Data Science).
• At least 3 years of industry experience with immunology or stromal biology.
• Experience analysing high-dimensional data such as RNAseq and proteomics and integrating diverse data sources.

Responsibilities

• Support progression of therapeutic molecules in early clinical development with in vitro/in vivo experiments.
• Set up translational assays including cell culture models and ex vivo cultures.
• Perform analysis of large datasets (RNAseq, scRNAseq, proteomics) using pipelines and tools.
• Collaborate with project teams to provide scientific insights for decision-making.
• Manage external CRO studies and ensure regulatory compliance.

Skills

Data analysis

Immunology

RNAseq

Proteomics

Team collaboration

Education

Degree or higher in Immunology, Systems Biology or Data Science

Tools

R

Python

Data analysis pipelines

Job description

Hyper Recruitment Solutions Ltd in the UK seeks a Research Data Scientist - Immunology to join a leading biopharmaceutical company. The role focuses on generating, analysing and translating preclinical data to inform immunology therapies, with an initial base at the current site before a move to Windlesham, Surrey, mid-2027.

You will work with interdisciplinary teams on translational research, analyze large datasets (RNAseq, scRNAseq, proteomics), and manage external CROs while ensuring