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
Training course
Data analyst (level 4)
Hours
Monday to Friday daytime. Shifts to be confirmed.
37 hours 30 minutes 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)
Other in:
* 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