Summary
Our apprentices enjoy a generous salary, 26 days of leave (excluding bank holidays), a £500 driving lesson contribution, and more. With a dedicated mentor and manager, you'll be supported every step of the way. We ask that you're eager to learn, work well in a team, and manage your time and workload effectively.
Wage
£20,000 a year
Yearly increase.
Training course
Data scientist (integrated degree) (level 6)
Hours
Monday - Friday, 37 hours, times to be confirmed.
37 hours a week
Possible start date
Wednesday 3 September
Duration
4 years
Positions available
1
Work
As an apprentice, you’ll work at a company and get hands-on experience. You’ll gain new skills and work alongside experienced staff.
What you’ll do at work
As an Apprentice Data Scientist, you’ll learn how to:
* Collaborate with regulatory and operational teams to understand data requirements, set up processes, identify trends, and deliver actionable insights
* Gather, clean, and preprocess large datasets to ensure accuracy/quality and consistency for analysis
* Develop skills in statistical analysis and create insightful reports to support regulatory submissions and compliance tracking
* Gain experience in building clear and informative dashboards and visualizations using tools like Power BI or Tableau to communicate findings effectively
* Work with databases, to retrieve, manipulate, and manage structured and unstructured data
* Use programming languages like Python or R to automate repetitive tasks, streamline workflows, and implement machine learning models for predictive analytics.
Where you’ll work
Haweswater House
Warrington
Cheshire
WA5 3LP
Training
An apprenticeship includes regular training with a college or other training organisation. At least 20% of your working hours will be spent training or studying.
College or training organisation
BPP PROFESSIONAL EDUCATION LIMITED
Your training course
Data scientist (integrated degree) (level 6)
Equal to degree
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.
Your training plan
Your apprenticeship will last 48 months, and successful apprentices will achieve a Data Scientist (integrated degree), Level: 6 standard, endorsed by the Institute for Apprenticeships.
Requirements
Essential qualifications
GCSE or equivalent in:
* Maths, English and a Science or Technology subject (grade A*-C or 9-4)
A Level in:
* including 1 STEM subject; a level 3 apprenticeship (grade A Level)
Let the company know about other relevant qualifications and industry experience you have. They can adjust the apprenticeship to reflect what you already know.
Skills
* Communication skills
* IT skills
* Attention to detail
* Organisation skills
* Problem solving skills
* Presentation skills
* Administrative skills
* Number skills
* Analytical skills
* Team working
* Initiative