Nestle Data Analyst Apprentice

Summary

Finished school or considering a career change? Ever thought about working in pensions? If not, maybe it’s time to! At Nestlé, our Pensions Team supports over 38,500 members and manages over £4 billion of assets, and you could be part of it. We are looking for someone who is eager to learn and loves working with data.

Annual wage: £24,375 a year
Minimum wage rates (opens in new tab)
Training course: Data analyst (level 4)
Hours: Monday to Friday daytime. Shifts to be confirmed.
37 hours a week
Possible start date: Monday 1 September
Duration: 2 years 6 months
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

Enuring compliance with regulatory requirements for common and conditional data tests
Collaborating closely with the Change and Technical Teams
Evaluate how changes affect our data needs and recording methods
Create and refine reliable, and repeatable procedures for data extraction and analysis
Staying updated on upcoming regulatory and technology developments that impact the fund’s data requirements, ensuring a proactive approach to evolving standards

Where you’ll work

Park House North

Crawley Business Quarter, Manor Royal

Crawley

RH10 9AD

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

CAMBRIDGE SPARK LIMITED

Your training course

Data analyst (level 4)

Equal to higher national certificate (HNC)

Course contents

Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
implement the stages of the data analysis lifecycle
apply principles of data classification within data analysis activity
analyse data sets taking account of different data structures and database designs
assess the impact on user experience and domain context on data analysis activity
identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
undertake customer requirements analysis and implement findings in data analytics planning and outputs
identify data sources and the risks and challenges to combination within data analysis activity
apply organizational architecture requirements to data analysis activities
apply statistical methodologies to data analysis tasks
apply predictive analytics in the collation and use of data
collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
select and apply the most appropriate data tools to achieve the optimum outcome
Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
implement the stages of the data analysis lifecycle
apply principles of data classification within data analysis activity
analyse data sets taking account of different data structures and database designs
assess the impact on user experience and domain context on data analysis activity
identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
undertake customer requirements analysis and implement findings in data analytics planning and outputs
identify data sources and the risks and challenges to combination within data analysis activity
apply organizational architecture requirements to data analysis activities
apply statistical methodologies to data analysis tasks
apply predictive analytics in the collation and use of data
collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
select and apply the most appropriate data tools to achieve the optimum outcome

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:

Maths & English Language (grade A*- C or 9-4)
Any (grade 96)

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
Administrative skills
Number skills
Analytical skills
Logical
Team working
Initiative

About this company

Good food nourishes and delights the senses. It helps pets to thrive, children to grow healthily and parents to age gracefully. It helps all of us to live life to the fullest. Good food also respects our planet and protects resources for future generations. But times are changing fast. And we know that what’s good today won’t be good enough tomorrow. Consider the challenge of satisfying the needs of 10 billion people by 2050 in a responsible and sustainable way. This will demand innovation and change. At Nestlé, we’re constantly pushing the boundaries of what’s possible with food, drink and nutritional health solutions. That way we can enhance quality of life and contribute to a healthier future for all. Today, our business has around 275,000 employees, more than 2,000 brands and a presence in 188 countries.

https://www.nestle.co.uk/en-gb (opens in new tab)

After this apprenticeship

By the end of your learning, you will have deepened your expertise with the potential to unlock opportunities
As well as this, you can choose to explore additional learning with the Pensions Management Institute, to support your development

Ask a question

The contact for this apprenticeship is:

CAMBRIDGE SPARK LIMITED

The reference code for this apprenticeship is VAC1000288845.

Apply now

Closes on Sunday 2 March

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After signing in, you’ll apply for this apprenticeship on the company's website.

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