Summary
In collaboration with our partnered training provider, Anglia Ruskin University, our 4-year degree apprenticeship scheme will enable you to grow and develop your capabilities.
Annual wage
£24,931 a year
Training course
Data scientist (integrated degree) (level 6)
Hours
08:30 to 16:45 Monday to Thursday, 08:30 to 16:15 Friday.
37 hours a week
Possible start date
Monday 8 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
* Working across a variety of projects, analysing data, and making suggestions that inform business decisions and improvements
* Development of core skills - data analytics, project management, and process improvement techniques/approaches
* Developing a good understanding of data structures and database systems
* Learning about and using a range of analytical tools
* Collecting, cleansing, abstracting and aggregating data
* Conducting a range of analytical studies on data
* Creating process and data workflows using tools such as Power Automate.
* Creating visualisations of data using tools like PowerBI and PowerApps
Where you’ll work
Frank Perkins Way
Peterborough
PE1 5FQ
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
ANGLIA RUSKIN UNIVERSITY HIGHER EDUCATION CORPORATION
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
Alongside on-the-job training supported by relatable mentors, apprentices will spend at least 20% of their working hours completing university-based learning leading to a nationally recognised qualification through the Level 6 Data Scientist apprenticeship standard:
Level 6 Data scientist Apprenticeship certificate.
BSc (Hons) Data Science.
Requirements
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
* Attention to detail
* Organisation skills