Data Science Apprentice (SPACE) - Pfizer
Cogent Ssc Limited
Tadworth, Surrey (KT20 7NS)
Closes on Friday 20 March 2026
Posted on 23 January 2026
Contents
Summary
Step into a dynamic, fast-paced environment where you’ll play a vital role in shaping global regulatory processes. This apprenticeship offers you the chance to work on meaningful projects that impact patients worldwide while developing skills that will set you apart in your future career.
- Wage
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£20,500 a year
- Training course
- Data scientist (integrated degree) (level 6)
- Hours
-
Monday to Thursday, 9am – 5.25pm. Fridays, 9am – 4.05pm.
12pm - 12.45pm lunch break.
37 hours a week
- Start date
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Tuesday 1 September 2026
- Duration
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3 years 6 months
- Positions available
-
1
Work
Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.
What you'll do at work
The regulatory environment is complex, highly data driven, and continuously evolving. This creates an ideal setting for an Apprentice to develop strong analytical and technical skills while contributing to meaningful organisational outcomes. As a Data Science Apprentice, you will work within Global Regulatory and International Operations and Quality Oversight to explore data, generate insights, and support the improvement of critical business processes.
Job Responsibilities
Data analysis & Insight Generation
- Source, access and manipulate regulatory and quality datasets to support decision‑making.
- Explore, profile, and transform data to ensure accuracy, quality and consistency.
- Apply statistical analysis and data‑science techniques to identify trends, risks, and opportunities for improvement.
- Visualise data through dashboards, reports and storytelling to communicate findings to technical and non‑technical audiences.
Compliance & Quality Oversight Through Data
- Analyse operational and compliance metrics to identify gaps, deviations or potential risks.
- Support the design of automated, data‑driven monitoring approaches to strengthen compliance oversight.
- Document, track and analyse compliance‑related issues, providing data‑supported recommendations for remediation.
- Present analytical findings, project updates and improvement proposals in meetings.
Business Process & System Design
- Participate in mapping and analysing existing business processes to identify inefficiencies and opportunities for automation.
- Support system testing, validation and optimisation of new or updated digital tools.
- Help define and document process requirements to ensure alignment with organisational, ethical and regulatory standards.
Process Re‑Engineering & Continuous Improvement
- Use analytical evidence to recommend process redesign or optimisation opportunities.
- Contribute to change‑management activities including impact assessments, stakeholder engagement and benefit analysis.
- Apply an inquisitive, hypothesis‑driven approach to test and evaluate new solutions.
What could you expect to gain?
- Experience working in a multidisciplinary team that oversees global processes where you are valued as a key member and pushed to develop as an individual.
- A broad range of important transferable skills including excellent communication, problem solving, data analysis, and adaptability enhancing your future employment opportunities.
- Knowledge on how different departments across Pfizer interact to work towards common goals and the pride of helping patients across the globe.
- Communicating insights through reporting, dashboards and data storytelling.
Where you'll work
Pfizer Ltd
Walton Oaks
Dorking Road
Tadworth, Surrey
KT20 7NS
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
UNIVERSITY OF NOTTINGHAM, THE
Training course
Data scientist (integrated degree) (level 6)
Understanding apprenticeship levels (opens in new tab)
What you'll learn
Course contents
- Identify and clarify problems an organisation faces, and reformulate them into Data Science problems. Devise solutions and make decisions in context by seeking feedback from stakeholders. Apply scientific methods through experiment design, measurement, hypothesis testing and delivery of results. Collaborate with colleagues to gather requirements.
- Perform data engineering: create and handle datasets for analysis. Use tools and techniques to source, access, explore, profile, pipeline, combine, transform and store data, and apply governance (quality control, security, privacy) to data.
- Identify and use an appropriate range of programming languages and tools for data manipulation, analysis, visualisation, and system integration. Select appropriate data structures and algorithms for the problem. Develop reproducible analysis and robust code, working in accordance with software development standards, including security, accessibility, code quality and version control.
- Use analysis and models to inform and improve organisational outcomes, building models and validating results with statistical testing: perform statistical analysis, correlation vs causation, feature selection and engineering, machine learning, optimisation, and simulations, using the appropriate techniques for the problem.
- Implement data solutions, using relevant software engineering architectures and design patterns. Evaluate Cloud vs. on-premise deployment. Determine the implicit and explicit value of data. Assess value for money and Return on Investment. Scale a system up/out. Evaluate emerging trends and new approaches. Compare the pros and cons of software applications and techniques.
- Find, present, communicate and disseminate outputs effectively and with high impact through creative storytelling, tailoring the message for the audience. Use the best medium for each audience, such as technical writing, reporting and dashboards. Visualise data to tell compelling and actionable narratives. Make recommendations to decision makers to contribute towards the achievement of organisation goals.
- Develop and maintain collaborative relationships at strategic and operational levels, using methods of organisational empathy (human, organisation and technical) and build relationships through active listening and trust development.
- Use project delivery techniques and tools appropriate to their Data Science project and organisation. Plan, organise and manage resources to successfully run a small Data Science project, achieve organisational goals and enable effective change.
Training schedule
Training for this apprenticship will be completed through block release to Nottingham University.
Requirements
Essential qualifications
GCSE in:
A Level in:
Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
Skills
- Communication skills
- IT skills
- Attention to detail
- Organisation skills
- Problem solving skills
- Administrative skills
- Number skills
- Analytical skills
- Logical
- Team working
- Creative
- Initiative
About this employer
As the specialists in skills for science and technology, our purpose is to make sure your business; your people and our industry are future ready. We are a not-for-profit charitable organisation with a family of commercially focused companies committed to supporting the skills, needs and ambitions across the UK science and technology sector.
Disability Confident
A fair proportion of interviews for this apprenticeship will be offered to applicants with a disability or long-term health condition. This includes non-visible disabilities and conditions.
You can choose to be considered for an interview under the Disability Confident scheme. You’ll need to meet the essential requirements to be considered for an interview.
After this apprenticeship
Upon successful completion of the apprenticeship, you will be eligible to apply for other positions within the business.
Ask a question
The contact for this apprenticeship is:
UNIVERSITY OF NOTTINGHAM, THE
The reference code for this apprenticeship is VAC2000010532.
Apply now
Closes on Friday 20 March 2026
After signing in, you’ll apply for this apprenticeship on the company's website.