Data Analyst Apprentice Level 4

Bernicia is offering a fantastic opportunity to join its Customer Insight & Engagement team as a level 4 Data Analyst Apprentice. You will explore the story behind the numbers, collecting, analysing and interpreting data supporting the business to make informed decisions.

You’ll learn on the job by getting hands-on experience.

Requirements

• A Level in Maths (grade C or above)
• A Level in another subject (grade C or above)
• Data Technician qualification (Pass)
• Other relevant qualifications and industry experience will be considered and may adjust the apprenticeship.
• Communication skills
• IT skills
• Attention to detail
• Organisation skills
• Customer care skills
• Problem solving skills
• Presentation skills
• Number skills
• Analytical skills
• Logical thinking
• Team working
• Initiative

Responsibilities

• Liaising with internal and external customers, collecting and compiling data
• Maintain and develop reports for analysis
• Analyse trends and patterns drawing conclusions
• Summarise and present data analysis reports
• Ensure data storage and archiving align with relevant legislation such as GDPR
• 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