Apprentice Data Scientist
R P S Group Ltd
Manchester (M1 4JB)
Closes in 15 days (Sunday 17 August 2025 at 11:59pm)
Posted on 1 August 2025
Contents
Summary
Are you passionate about data, analytics, and using numbers to solve real-world problems? RPS, a Tetra Tech company, is looking for an Apprentice Data Scientist to start your career in data science within an environmental consultancy setting, gaining practical experience while developing your skills and knowledge.
- Wage
-
£21,000 a year
Check minimum wage rates (opens in new tab)
Annual salary increase - dependant on successful performance review
- Training course
- Data scientist (integrated degree) (level 6)
- Hours
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Monday - Friday, 9.00am - 5.30pm
3-4 days a week in the office in the first year, with a review every 3 months
37 hours 30 minutes a week
- Start date
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Monday 5 January 2026
- Duration
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3 years
- Positions available
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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
- Assist with data collection, cleaning, and exploratory analysis using statistical software and programming languages
- Support development of models, visualisations, and reports to communicate insights effectively
- Work closely with multidisciplinary teams to integrate data science outputs into projects
- Follow data governance and quality assurance protocols
- Engage in continuous learning through your apprenticeship course to build your skills towards a BSc degree or equivalent qualification
Where you'll work
5 New York Street
Manchester
M1 4JB
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
MANCHESTER METROPOLITAN UNIVERSITY
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
- Data scientist (integrated degree) Level 6 (Degree with honours)
- Manchester Metropolitan University - One day a week
- RPS Manchester Office - Hybrid
Requirements
Essential qualifications
A Level in:
Desirable qualifications
GCSE in:
Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
Skills
- IT skills
- Attention to detail
- Organisation skills
- Problem solving skills
- Number skills
- Logical
- Team working
- Initiative
- Patience
- statistical knowledge
- analytical mindset
About this employer
RPS is a leading global multi-disciplinary consultancy. We specialise in all areas of the built and natural environment, shaping the future of our environmental, social and economic landscapes.
http://www.rpsgroup.com (opens in new tab)
Company benefits
Cycle to work scheme Pension
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
- Data Analyst
- Geospatial Data Analyst
- Data Engineer
- Data Manager
Ask a question
The contact for this apprenticeship is:
MANCHESTER METROPOLITAN UNIVERSITY
The reference code for this apprenticeship is VAC1000335101.
Apply now
Closes in 15 days (Sunday 17 August 2025 at 11:59pm)
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