Data Scientist – Applied Immunology

JR United Kingdom; Sheffield; Hybrid; GBP 45,000 - 65,000; Full time

Job summary

JR United Kingdom is seeking a Data Scientist specializing in Applied Immunology to join their data team in Sheffield. This role involves designing and scaling analysis to extract insights from complex immune data, with opportunities for substantial growth and impact in the field. Candidates should possess strong data science expertise and a collaborative mindset to bridge biological and computational domains.

Qualifications

• 2-5 years experience in applied data science or ML engineering, ideally in life sciences.
• Clean, reproducible Python coding skills.
• Experience with building and evaluating ML models.

Responsibilities

• Own and evolve data analysis pipelines built in Python and R.
• Contribute to modeling projects using ML.
• Collaborate with scientists for interpretable outputs.

Skills

Data Science

Machine Learning

Python

R

Statistical Modeling

Education

Bachelor's degree in Life Sciences or related field

Experience in Applied Data Science or ML Engineering

Tools

Kedro

SageMaker

Docker

Job description

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Data Scientist – Applied Immunology, Sheffield, South Yorkshire

Location: Sheffield, South Yorkshire, United Kingdom

Job Category: Other

EU work permit required: Yes

Job Views: 3

Posted: 04.06.2025

Expiry Date: 19.07.2025

Job Description:

Location: London UK / Hybrid

Team: Data Science | IMU Biosciences

Role Type: Full-time, Individual Contributor (with growth pathways)

About IMU Biosciences: IMU is building the next generation of immune intelligence—machine learning and AI models that decode the complexity of the human immune system to improve patient outcomes.

We work at the intersection of single cell technologies, machine learning, AI, and clinical immunology, turning high-dimensional immune data into signatures that inform clinical and translational decisions. Our vision is to build the world’s most insightful immune analytics platform—combining deep biological data and cutting-edge machine learning with rigorous systems-level reasoning.

About the Role

We’re looking for a scientifically curious, systems-minded Data Scientist to join our growing data team. This is a key hire to support the next phase of our platform and product development.

You'll be joining IMU as an essential part of a team that spans discovery biology, statistical modeling/machine learning, and software engineering—with direct exposure to our clinical collaborators, lab team, and leadership.

This is not a typical “data munging” role.

You’ll help us design, build, and scale how we extract meaning from complex immune data—working on problems like:

• How does immune variation between individuals contribute to outcome across a diverse range of diseases and treatments?
• How do we unify, and exploit, complex multimodal large-scale immune datasets?
• Building self-service tools for our scientists to interrogate and visualise results easily and safely.

What You'll Do

In the first 6 months:

• Own and evolve pipelines built in Python and R (and Kedro and SageMaker) to analyse immune profiles.
• Contribute to modelling projects that use ML to identify immune signatures of disease or treatment outcomes.
• Support internal tooling that connects lab outputs, data cleaning, and model-ready datasets.
• Collaborate with scientists and lab staff to ensure outputs are interpretable and actionable.

In the next 12 months:

• Drive forward specific components of our immune analytics platform (e.g., prediction, signature interpretation, batch and drift monitoring and correction).
• Help shape internal standards for data documentation, reproducibility, and metadata management.
• Potential to carve out ownership over a specific domain: e.g., model validation, ontologies, scientific interfaces.

You Might Be a Fit If You:

• Have 2–5 years experience in applied data science or ML engineering, ideally in life sciences or health data.
• Write clean, reproducible Python and understand workflow tools like Kedro, Dagster, or other orchestration platforms.
• Have built and evaluated ML models for real-world use cases (especially classification or regression with limited samples).
• Are excited by biological complexity: You don’t need to be an immunologist, but you need to respect the nuance.
• Think in systems: You naturally refactor, generalise, and leave things better than you found them.
• Care deeply about scientific rigor, traceability, and experimental design.

Bonus (but not required)

• Experience with flow cytometry, single cell sequencing, antigen receptor sequencing or other high-dimensional single-cell assays.
• Familiarity with batch effect correction, signal drift, or statistical learning in low-n cohorts.
• Exposure to knowledge management systems, ontologies, or scientific metadata.
• AWS/SageMaker, Kedro and/or Dagster tooling or containerised workflows (Docker, CI/CD).

What It’s Like to Work Here

At IMU Biosciences, you’ll join a high-trust, low-ego team united by shared values and a drive to make meaningful impact. We believe in:

• Calm intensity: We work with purpose and clarity—focused, deliberate, and resilient.
• Scientific integrity: We follow where the data leads, even when it challenges our assumptions.
• Platform mindset: We aim to solve problems once and scale them effectively across our workflows.
• Cross-disciplinary fluency: We bridge disciplines—data science, software engineering, immunology, and clinical research—to build solutions that make sense from all angles.

We value autonomy, avoid micromanagement, and stay grounded in results over hype. Insight and impact drive us.

How to apply

Send us your CV and a short note about why this role feels right to you. If you have links to code, notebooks, or publications – great. If not, no problem. We care more about how you think than how polished your résumé is.

To apply please send a cover letter and CV to: [emailprotected]. We do not accept unsolicited emails from recruitment agencies.

https://www.imubiosciences.com/jobs/data-scientist-applied-immunology/