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Early Career) Information Scientist

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Early Career) Information Scientist
Early Career Information Scientist - Content Analytics & Data Science
Type: Temporary Duration: 12 months Location: Slough (Hybrid – minimum 2 days onsite) Rate:
- PAYE: up to £22.40 per hour (INSIDE IR35)
- Umbrella: up to £30.81 per hour
SRG are supporting a leading pharmaceutical company with an opportunity for an Early Career Information Scientist to join a scientific information and intelligence team.
About the Role
This exciting role aims to develop expertise in data science, AI-enabled analytics, and scientific information management within an advanced R&D environment. Based in Slough with hybrid working options, this position focuses on transforming scientific content and data into practical insights using a combination of programmatic and analytical approaches.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Responsibilities
- Develop and maintain automated programmatic workflows to support scientific data analysis.
- Apply data science techniques to identify trends, patterns, and insights from scientific information.
- Build and optimise automated pipelines for content analytics and data processing.
- Utilise AI and Natural Language Processing (NLP) tools for text mining and summarisation activities.
- Collaborate with cross-functional stakeholders to support information and analytics projects.
- Contribute to data governance initiatives and responsible AI practices.
Skills & Experience Required
- A degree in Life Sciences, Data Science, Bioinformatics, or a closely related discipline.
- Basic programming skills with a willingness to develop technical capabilities.
- Strong analytical and problem-solving skills with a keen attention to detail.
- Interest in applying data-driven approaches to scientific research and information management.
- Experience (or exposure) to:
- Natural Language Processing (NLP)
- Machine learning
- Scientific data analysis (advantageous)
- Familiarity with metadata, ontologies, or knowledge graphs (beneficial).


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How to Apply
To discuss further or submit your application, please contact Theo Charles (contact details provided).
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