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- Tasks: Analyse data to drive insights on customer behaviour and product performance.
- Company: Join a forward-thinking organisation that values curiosity and innovation.
- Benefits: Enjoy structured support, real responsibility, and clear career development opportunities.
- Why this job: Make a real impact on business decisions and improve customer outcomes.
- Qualifications: A degree in a numerate subject and strong analytical skills are essential.
- Other info: Work within a high-performing team and engage with diverse data sets.
The predicted salary is between 28800 - 48000 £ per year.
The vacancy represents a fantastic opportunity to apply analysis and modelling skills to drive meaningful commercial insight within a mass customer-centric business function. Ideal for a recent graduate or early-career professional, this role sits within a high-performing Information Management team and offers the chance to work directly with product, customer, and campaign data to support strategic decision-making.
You’ll support the delivery of insight across customer behaviour, product performance, marketing campaigns, and complaint trends. Your work will influence business actions and improve customer outcomes.
Responsibilities:- Develop and maintain customer data models and reporting tools.
- Analyse trends across products, customers, campaigns, and complaints.
- Respond to ad-hoc data queries with clear, actionable insight.
- Maintain and enhance customer prompt processes and marketing campaign support.
- Create accurate customer mailing files and contribute to campaign targeting.
- Develop customer profiles to provide deeper behavioural understanding and track changes over time.
- Deliver complaint reporting on schedule for both internal use and external requirements.
- Act as the main point of contact for explaining analysis and presenting findings to stakeholders.
- A degree in a numerate or analytical subject (e.g. Mathematics, Economics, Statistics, Data Science, Business Analytics).
- A naturally analytical mindset with strong attention to detail.
- Solid knowledge of Excel and familiarity with tools like Power BI.
- Exposure to data mining or reporting tools (e.g. SPSS, SQL, Business Objects, or similar).
- Ability to work independently with complex data sets and deliver clear insights.
- Confidence in communicating data stories to both technical and non-technical audiences.
- A proactive, solutions-focused approach and a genuine interest in data-led decision-making.
You’ll be joining a forward-thinking organisation that values curiosity, data, and innovation. This role offers structured support, real responsibility, and clear career development in a collaborative and insight-led environment.
Please apply for further job & interview details.
Graduate Data Analyst employer: MSA Data Analytics Ltd
Contact Detail:
MSA Data Analytics Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Data Analyst
✨Tip Number 1
Familiarise yourself with the tools mentioned in the job description, such as Excel and Power BI. Consider taking online courses or tutorials to enhance your skills, as this will not only boost your confidence but also demonstrate your commitment to the role.
✨Tip Number 2
Network with professionals in the data analysis field, especially those who work in customer-centric businesses. Attend industry events or join relevant online forums to gain insights and potentially make connections that could lead to referrals.
✨Tip Number 3
Prepare to discuss real-world examples of how you've used data to drive decisions or insights in your previous projects or studies. This will help you articulate your analytical mindset and problem-solving skills during interviews.
✨Tip Number 4
Stay updated on current trends in data analysis and customer behaviour. Being knowledgeable about the latest developments in the field will allow you to engage in meaningful conversations during interviews and show your genuine interest in the role.
We think you need these skills to ace Graduate Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences that align with the Graduate Data Analyst role. Emphasise your analytical mindset, attention to detail, and any experience with data tools like Excel or Power BI.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data analysis and how your academic background prepares you for this role. Mention specific projects or coursework that demonstrate your ability to analyse data and derive insights.
Showcase Relevant Skills: In your application, clearly outline your proficiency in data mining and reporting tools. If you have experience with SQL or SPSS, be sure to mention it, as these are valuable skills for the position.
Prepare for Potential Questions: Think about how you would explain complex data findings to both technical and non-technical audiences. Be ready to discuss your approach to problem-solving and how you can contribute to the company's data-led decision-making.
How to prepare for a job interview at MSA Data Analytics Ltd
✨Showcase Your Analytical Skills
Be prepared to discuss your analytical mindset and how you've applied it in your studies or previous roles. Use specific examples to demonstrate your ability to analyse data and derive actionable insights.
✨Familiarise Yourself with Tools
Make sure you have a good understanding of Excel, Power BI, and any other relevant data tools mentioned in the job description. You might be asked about your experience with these tools, so having examples ready will help you stand out.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. The role requires you to present findings to both technical and non-technical audiences, so being able to communicate effectively is key.
✨Demonstrate Proactivity
Show your proactive approach by discussing instances where you've taken the initiative to solve problems or improve processes. This aligns well with the company's values and will highlight your fit for the role.
