Data Analyst Apprentice

We are looking for a passionate Junior Data Analyst. The successful candidate will have a keen eye for detail, a willingness to learn and an understanding of the link between data, insights, and business decisions.

Requirements

• A good understanding of data concepts, particularly around structured and semi-structured data sets.
• Theoretical knowledge of SQL language. Any working experience would be a plus.
• Knowledge of at least one programming language (e.g., Python, R, Java, C#).
• Proficiency in the use of Microsoft Excel.
• Experience of Microsoft Power BI would be a plus.
• Understanding of ETL platforms would be a plus.
• Strong analytical skills with the ability to collect, organise, analyse, and disseminate significant amounts of information with attention to detail and accuracy.
• Good level of maths.
• A Level in Computer Science (grade B).
• A Level in Maths (grade B).
• Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
• Communication skills
• Problem solving skills
• Number skills
• Analytical skills
• Logical
• Ambitious, energetic, and people-focused individual who genuinely enjoys building relationships and helping businesses succeed.
• Confident communicator, proactive problem-solver, and natural networker who thrives in a fast-paced environment.
• Self-motivated, organised, and comfortable engaging with business owners, attending events, generating opportunities, and representing our brand within the local community.
• A positive attitude, strong work ethic, and passion for supporting local businesses are essential.
• Experience in sales, marketing, customer service, networking, or business development would be advantageous.

Responsibilities

• Develop and implement databases, data collection systems and data engineering solutions that optimise reporting efficiency and clarity.
• Acquire data from primary or secondary data sources and maintain databases/data lakes.
• Interpret data, analyse results using statistical techniques and provide ongoing reports.
• Identify, analyse, and interpret trends or patterns in complex data sets.
• Filter and “clean” data by reviewing raw data, reports, and performance indicators to locate and correct code problems.
• Work with management to prioritise business and information needs.
• Locate and define new process improvement opportunities.
• 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.