Summary
Do you want to learn and work with a global leader in skills development? City & Guilds are delighted to be recruiting for a Data Science Apprentice. Positioned in a hybrid team, you will work on a full time (35 hours) basis for the duration of your apprenticeship. This is a permanent position on the condition of completing the apprenticeship.
Wage
£18,000 a year
You’ll receive an increment at 1 year, 2 years and on completion
Training course
Data scientist (integrated degree) (level 6)
Hours
Monday - Friday, between 9.00am to 5.00pm.
35 hours a week
Possible start date
Thursday 1 May
Duration
1 year 8 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
* Developing and implementing reproducible analytical pipelines to deliver routine outputs.
* Building expertise in quantitative analyses and interactive analytics using tools such as R and Shiny.
* Working collaboratively with internal teams, customers, partners and stakeholders to deliver projects.
* Disseminating outputs of analyses to technical and non-technical audiences internally and externally.
* Championing data quality principles and embedding good practice.
* Developing your own technical expertise in the vocational education sector.
Where you’ll work
This apprenticeship is available in these locations:
* 1 Newlands Court, Attwood Road, Burntwood, WS7 3GF
* 5-6 Giltspur House, London, EC1A 9DE
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
College or training organisation
CORNDEL 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
This training plan has not been finalised. Check with this employer if you’ll need to travel to a college or training location for this apprenticeship.
Requirements
Essential qualifications
GCSE in:
* English (grade Pass)
A Level in:
* Maths (grade Pass)
Desirable qualifications
A Level in:
* ICT (grade Pass)
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
* IT skills
* Attention to detail
* Organisation skills
* Problem solving skills
* Number skills
* Analytical skills
* Team working
* Technology
* Statistics