Summary
Veolia is looking for a Procurement Data Science Degree Apprentice to join their team in Cannock.
Wage
£25,105 a year
Pay will increase after one year.
Training course
Data scientist (integrated degree) (level 6)
Hours
Monday - Friday, Shifts be confirmed. 30-minute break.
40 hours a week
Possible start date
Wednesday 3 September
Duration
5 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
* Learning to manage and analyse procurement data, ensuring accuracy and reliability.
* Assisting the Procurement team in making informed decisions based on data insights.
* Helping to develop and implement data solutions that enhance our procurement processes.
* Supporting projects aimed at improving efficiency and automation in procurement.
* Creating clear and concise reports on procurement data for various team members.
* Collaborating with different departments to understand their data needs and requirements.
* Gaining hands-on experience with cutting-edge technologies, including AI-driven solutions for procurement.
* Contributing to initiatives that optimise our ways of working and track the benefits of our procurement strategies.
Where you’ll work
Kingswood House
Kingswood Crescent
Cannock
WS11 8JP
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
CRANFIELD UNIVERSITY
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
* Level 6 Data Scientist Integrated Degree.
* 20% off the job training, method and location to be confirmed.
* Endpoint assessment.
Requirements
Essential qualifications
GCSE or equivalent in:
* English and Math's (grade 4/C or above)
A Level in:
* Mathematics, IT or a Data Science field (grade Level 3)
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
* Customer care skills
* Problem solving skills
* Administrative skills
* Initiative