Marketing Data Analysis Apprentice in Reading

Marketing Data Analysis Apprentice in Reading

Reading Full-Time 800 - 1000 £ / month (est.) No working from home possible
QA

At a Glance

  • Tasks: Dive into data analysis, optimise digital marketing, and support reporting tasks.
  • Company: 51Degrees, a leading tech company in device intelligence and analytics.
  • Benefits: Hybrid working, professional development, and a supportive mentoring environment.
  • Other info: 90% of apprentices secure permanent roles after completing the programme.
  • Why this job: Kickstart your career with hands-on experience in a dynamic marketing role.
  • Qualifications: Strong analytical skills, attention to detail, and a willingness to learn.

The predicted salary is between 800 - 1000 £ per month.

About 51Degrees: 51Degrees is a leading technology company specialising in device intelligence, digital performance analytics, and data-driven insights. This apprenticeship role offers hands-on experience across analytics, website performance, competitor research and digital optimisation.

About the role: An opportunity for a Marketing Data Analysis Apprentice based in Central Reading, with hybrid options post-probation. The apprentice will enrol onto a Level 3 programme with progression opportunities. The role supports digital marketing, reporting, analytics and optimisation.

Responsibilities:

  • Resolve 404 errors and ensure correct redirections
  • Maintain consistent UTM parameters
  • Review and update open-source package pages
  • Monitor Core Web Vitals and report findings
  • Track competitor updates and support fortnightly reporting
  • Prepare initial drafts of online performance reports
  • Complete delegated tasks from the Marketing Lead

What we are looking for:

  • Strong analytical thinker
  • Excellent attention to detail
  • Problem-solving mindset
  • Good written communication
  • Ability to use spreadsheets and online tools
  • Organised and willing to learn

Additionally, the following experience would be beneficial:

  • Awareness of SEO and digital marketing
  • Familiarity with analytics tools
  • Understanding of UTM tracking
  • Basic HTML/CMS knowledge
  • Awareness of Core Web Vitals

Entry requirements:

  • 3 GCSEs (or equivalent) at grades 4+ (A-C) in any subject
  • GCSE Maths and English (or equivalents) at grades 3+ (D or above)
  • Prospective apprentices must not hold an existing qualification at the same or higher level as this apprenticeship in a similar subject

You may also have a combination of qualifications and experience which demonstrate the minimum foundation needed for the programme. In this instance you could still be considered for the programme. If you hold international equivalents of the above qualifications, at the time of your application you must be able to provide an official document that states how your international qualifications compare to the UK qualifications.

Working hours: Monday to Friday, 9am - 5.30pm. First 3-months are 100% office based, then hybrid following this. It will then be 3 days in the office, and 2 days at home.

Benefits:

  • Hybrid working post-probation
  • Professional development and training opportunities
  • Supportive mentoring environment
  • Clear progression pathway
  • Modern office environment

Future prospects:

90% of QA apprentices secure permanent employment after completing: this is 20% higher than the national average.

About QA: Our apprenticeships are the perfect way to gain new skills, earn while you learn, and launch yourself into an exciting future. With over 50,000 successful apprenticeship graduates, we are a top 50 training provider, dedicated to helping you succeed.

Interested? Apply now!

Please be advised that this advert may close prior to the closing date stated above if a high number of applications are received. If you are interested in this vacancy please apply below as soon as possible.

Marketing Data Analysis Apprentice in Reading employer: QA

51Degrees is an exceptional employer that offers a dynamic and supportive work culture in Central Reading, where apprentices can thrive in a modern office environment. With a strong focus on professional development, mentoring, and clear progression pathways, employees are empowered to grow their skills in digital marketing and analytics. The hybrid working model post-probation further enhances work-life balance, making it an attractive opportunity for those seeking meaningful and rewarding employment.

QA

Contact Details:

QA Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Marketing Data Analysis Apprentice in Reading

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like QA!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Marketing Data Analysis Apprentice at QA.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like QA.

Apply Directly through Our Website

When you find a suitable opening like Marketing Data Analysis Apprentice at QA, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Marketing Data Analysis Apprentice in Reading

Analytical Thinking
Attention to Detail
Problem-Solving Mindset
Written Communication
Spreadsheet Proficiency
Organisational Skills
SEO Awareness

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at QA, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at QA. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at QA

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at QA!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.