Junior Data Scientist - NLP/text mining

Hays Life Sciences
London, United Kingdom
Today
£175 – £275 pd

Salary

£175 – £275 pd

Job Type
Contract
Work Pattern
Full-time
Work Location
Hybrid
Seniority
Junior
Education
Degree
Posted
10 Jul 2026 (Today)

Benefits

Flexible working Supportive colleagues Learning and training opportunities

Your new company

You'll be joining a global biopharmaceutical organisation supporting scientific information, intelligence, and data-driven decision-making across research and development as part of a highly experienced team with plenty of learning and training opportunities.

The company has a highly collaborative environment where data science, AI, and scientific expertise are combined to generate insights from biomedical information sources.

Your new role

You'll be part of the company's R&D department, working as an Early Career / Junior Information Scientist to support the development of computational approaches for analysing scientific content and external data sources. This will be used to optimise the company's drug discovery and development plans across multiple disease areas.

This is initially a 12-month contract that may extend and requires several days per week on site (likely 2-3 days per week home/remote working).

Key responsibilities include:

Developing and supporting automated workflows for scientific data analysis

Applying data science and analytical techniques to identify trends and generate insights from biomedical / pharmaceutical data

Building and maintaining content analytics pipelines

Using AI, NLP, and text-mining approaches to analyse biomedical literature and scientific datasets

Supporting the extraction, organisation, and interpretation of scientific information

Collaborating with cross-functional stakeholders across research and development

Contributing to data governance and responsible AI initiatives

Supporting scientific information and intelligence activities through data-driven approaches

All candidates MUST hold the full right to work for the entire length of the contract (likely at least September 2027) as no sponsorship is available. Candidates without this cannot be considered.

What you'll need to succeed

A strong candidate will combine scientific understanding with an interest in coding, analytics, and emerging AI technologies and should also have:

A BSc / MSc (or equivalent experience) in Life Sciences, Data Science, Bioinformatics, Computational Biology, Computer Science, or a related field

Good programming skills (e.g. Python, R, or similar)

Strong analytical and problem-solving abilities

An interest in data science, content analytics, and scientific information management - ideally with demonstrable work experience in this field

The ability to work effectively with both scientific and technical stakeholders

Strong communication and organisational skills as regular interaction with a range of stakeholders is a core part of the job

Experience with NLP, machine learning, scientific datasets, or biomedical literature is a significant advantage - preferably gained from working in a pharmaceutical, biotech diagnostics, CRO or consultancy company supporting drug discovery / development projects

Familiarity with metadata, ontologies, knowledge graphs, or information retrieval concepts is beneficial

Full right to work in the UK

What you'll get in return

You'll get the chance to build your career within a fast-paced and highly innovative pharmaceutical company and make a real impact on some of their early drug discovery programmes.

You'll also have flexible working, supportive colleagues and a good daily rate.

What you need to do now

If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.

If this job isn't quite right for you but you are looking for a new position, please contact us for a confidential discussion on your career.

Keywords: Information, Scientist, Data, Analytics, Science, Research, Pharmaceutical, AI, NLP, Text mining, Machine, learning, Python, R, Informatics, Literature, Biomedical, Insights, Metadata, Ontologies, Knowledge, graphs, Automation, Programming, Intelligence, Content, Mining, Bioinformatics, Computation, analysis, Governance, Innovation

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