Open roleExternal
Apprentice Data Analyst
- manchester, greater manchester, M1 1AE, United Kingdom
- Hybrid
- £21,000 - £21,000 Per Annum
Job Description
About the Role
Our client is searching for a curious and analytical Apprentice Data Analyst to join their team in Manchester . This role offers a unique pathway into the field of data science and business intelligence. You will work with large datasets, learning to extract, clean, and interpret information to provide actionable insights that support strategic decision-making. The position involves collaborating with various departments to understand their data needs and presenting findings in a clear and concise manner. This is an ideal opportunity for individuals who are passionate about numbers and eager to develop advanced analytical skills in a supportive, hybrid work environment.
Key Responsibilities
- Assist in collecting and cleaning data from various sources, ensuring accuracy and integrity.
- Learn to perform data analysis using tools like Excel, SQL, and potentially Python or R.
- Help create reports, dashboards, and visualizations to communicate findings effectively.
- Support the identification of trends, patterns, and anomalies within datasets.
- Collaborate with stakeholders to understand their data requirements and reporting needs.
- Contribute to the development of data models and data quality frameworks.
Requirements
- A keen interest in data analysis, statistics, and problem-solving.
- Proficiency with Microsoft Excel is essential; experience with SQL is a plus.
- Strong analytical and critical thinking skills.
- Good communication and presentation skills, both written and verbal.
- Ability to manage multiple tasks and meet deadlines in a hybrid work setting.
- Commitment to completing the apprenticeship program and continuous learning.
Benefits
- Hands-on training in data analysis tools and techniques.
- Mentorship from experienced data professionals.
- Competitive apprentice salary with opportunities for progression.
- Exposure to diverse business challenges and data-driven solutions.
- Hybrid working model offering a balance between office collaboration and remote flexibility.