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For Companies At a Glance
- Tasks: Transform raw data into actionable insights and support strategic initiatives.
- Company: Join mrkit, where data drives every decision in a collaborative environment.
- Benefits: Enjoy competitive salary, health insurance, flexible work, and professional development opportunities.
- Why this job: Make a real impact by analysing diverse datasets and shaping business growth.
- Qualifications: Bachelor’s degree in a related field and experience with SQL and data visualisation tools.
- Other info: Work in a dynamic, fast-paced environment with access to cutting-edge technologies.
The predicted salary is between 28800 - 48000 £ per year.
About the Role
At mrkit, data drives every decision we make. As a Data Analyst, you will play a crucial role in transforming raw data into actionable insights that empower our teams and shape the future of our business. This position offers an exciting opportunity to work with diverse datasets, collaborate across departments, and contribute to strategic initiatives that impact our growth and innovation.
Key Objectives
- Analyse complex data sets to identify trends, patterns, and opportunities.
- Provide clear, data-driven insights to support business decisions.
- Collaborate with cross-functional teams to develop and optimize reporting tools.
- Ensure data accuracy and integrity through rigorous validation and quality checks.
Responsibilities
- Collect, process, and analyse large volumes of structured and unstructured data.
- Create and maintain dashboards, reports, and visualizations to communicate findings effectively.
- Work closely with stakeholders to understand their data needs and deliver tailored solutions.
- Identify data quality issues and recommend improvements to enhance data reliability.
- Support the development of predictive models and advanced analytics initiatives.
- Stay current with industry trends and best practices in data analysis and visualization tools.
Requirements
- Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, or a related field.
- Proven experience as a Data Analyst or in a similar analytical role.
- Strong proficiency in SQL and experience with data visualization tools such as Tableau, Power BI, or Looker.
- Hands-on experience with statistical analysis and data manipulation using Python, R, or similar languages.
- Excellent problem-solving skills and attention to detail.
- Ability to communicate complex data insights clearly to non-technical audiences.
- Experience working in a collaborative, fast-paced environment.
Preferred Qualifications
- Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
- Familiarity with machine learning concepts and applications.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
Benefits
- Competitive salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance plans.
- Generous paid time off and flexible work arrangements.
- Opportunities for professional development and continuous learning.
- Collaborative and inclusive company culture that values innovation.
- Access to cutting-edge tools and technologies.
Data Analyst in Glasgow employer: mrkit
Contact Detail:
mrkit Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst in Glasgow
✨Tip Number 1
Network like a pro! Reach out to current or former employees at mrkit on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects. Use real-world examples that highlight your ability to turn raw data into actionable insights, just like you'd do at mrkit.
✨Tip Number 3
Prepare for the interview by brushing up on your SQL and data visualisation tools. Be ready to discuss how you've used these skills to solve problems in past roles – it’s all about demonstrating your value!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team at mrkit.
We think you need these skills to ace Data Analyst in Glasgow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Analyst role. Highlight your experience with SQL, data visualisation tools, and any relevant projects that showcase your analytical skills. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data analysis and how your skills align with our objectives at mrkit. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any interesting data projects, don’t hesitate to include them in your application. Whether it's a dashboard you built or a predictive model you developed, we want to see your hands-on experience and creativity!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at mrkit
✨Know Your Data Tools
Make sure you brush up on your SQL skills and get familiar with data visualisation tools like Tableau or Power BI. Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of the role.
✨Showcase Your Analytical Skills
Prepare to talk about specific examples where you've analysed complex datasets. Highlight any trends or insights you discovered and how they impacted decision-making. This will demonstrate your ability to turn raw data into actionable insights.
✨Communicate Clearly
Practice explaining your findings in a way that non-technical stakeholders can understand. Use simple language and avoid jargon. Being able to communicate complex data insights clearly is crucial for a Data Analyst.
✨Stay Current with Industry Trends
Familiarise yourself with the latest trends in data analysis and visualisation. Mention any recent developments or tools you've learned about, as this shows your commitment to continuous learning and staying ahead in the field.
