Data Analyst Apprentice
QA Apprenticeships, Mount Hermon, Woking
Data Analyst Apprentice
Salary not available. View on company website.
QA Apprenticeships, Mount Hermon, Woking
- Full time
- U
- Onsite working
- Apprenticeship programme
Posted 1 week ago, 23 Oct | Get your application in now before you're too late!
Closing date: Closing date not specified
job Ref: a3405ef816b64e708a11403215a8379f
Full Job Description
- Data Collection: Gather and collate data from various sources, including internal systems, databases, and external sources, ensuring accuracy and completeness.
- Data Cleansing: Cleanse and preprocess data to remove inconsistencies, errors, and duplicates, ensuring data integrity and reliability for analysis.
- Data Analysis: Utilise statistical techniques and data analysis tools to analyse large datasets, extract meaningful insights, and identify trends and patterns relevant to business objectives.
- Data Visualisation: Create visualisations, dashboards, and reports to present findings and insights in a clear and concise manner, enabling stakeholders to make informed decisions.
- Data Interpretation: Interpret and communicate findings to key stakeholders, providing actionable recommendations and insights to support strategic initiatives and business growth.
- Data Governance: Adhere to data governance policies and procedures, ensuring compliance with regulatory requirements and best practices for data management and security.
- Continuous Learning: Stay abreast of emerging trends, technologies, and best practices in data analysis, seeking opportunities for continuous learning and professional development.
Experience with Excel (in particular pivot tables and XLookup) and Microsoft products (or similar) - Genuine interest in data analysis and a passion for leveraging data to drive business outcomes.
- Strong analytical and problem-solving skills, with proficiency in statistical analysis and data visualisation tools.
- Excellent attention to detail and the ability to work with large datasets.
- Effective communication skills and the ability to translate complex data insights into actionable recommendations. Entry requirements: Standard entry:
- Level 3 qualification (apprenticeship/A-levels/BTEC, etc)
- OR equivalent work experience (typically two years in a relevant role) Plus:
- 5 GCSE's, including English and Maths at Grade 4 (C) or above
- Experience with using Excel (in particular pivot tables and XLookup) and Microsoft products (or similar)
QA Apprenticeships Woking Employer description: McLaren Automotive, renowned for its innovative approach to automotive engineering and design, continues to lead the industry in luxury sports car manufacturing. As part of our commitment to excellence, we offer apprenticeship opportunities that provide hands-on experience and a pathway to a rewarding career in data analysis., Our apprenticeships are the perfect way to gain new skills, earn while you learn, and launch yourself into an exciting future. With over 30,000 successful apprenticeship graduates, we're a top 50 training provider, dedicated to helping you succeed. - Competitive apprenticeship salary
- Hands-on training and mentorship from experienced data analysts
- Exposure to cutting-edge data analysis tools and techniques
- Opportunities for career advancement within McLaren Automotive As well as:
- 25 days' holiday, plus bank holiday
- Private medical insurance and health cash plan
- Life assurance 4x your basic salary
- Benefits you can adapt to your lifestyle, such as discounted shopping
- Generous parental leave policies including market leading maternity leave
- Tax efficient nursery scheme benefit
- A range of wellbeing initiatives, such as employee assistance programme and free financial & mortgage advice
- Friends and family day
- Enhanced company pension scheme Future prospects: 90% of QA Apprentices secure permanent employment after finishing their apprenticeship. Additionally, there may be opportunities to undertake further apprenticeship training as many of our programs offer on-going development tracks.