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- Tasks: Create data-driven products and insights for the insurance market using Power BI.
- Company: Leading data solutions company with a focus on innovation.
- Benefits: Competitive salary, 25 days annual leave, and hybrid working options.
- Why this job: Join a dynamic team and shape the future of data in insurance.
- Qualifications: Experience with Power BI and strong data analysis skills.
- Other info: Full-time permanent role with great career growth potential.
The predicted salary is between 36000 - 60000 £ per year.
A leading data solutions company is seeking a Product Data Analyst to develop data-driven products and insights for the insurance market. You will design dashboards and models using Power BI, collaborate across teams, and contribute to product innovation.
The role offers competitive salary, 25 days annual leave, and hybrid working arrangements.
Essential qualifications include experience with Power BI and strong data analysis skills. This is a full-time permanent position located in the Greater London area.
Product Data BI Analyst - Hybrid London employer: Wilmington plc
Contact Detail:
Wilmington plc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Product Data BI Analyst - Hybrid London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in data analytics or insurance. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Power BI dashboards and data models. This visual evidence of your expertise can really make you stand out during interviews.
✨Tip Number 3
Prepare for those interviews! Research common questions for Product Data Analysts and practice your answers. We recommend using the STAR method to structure your responses and highlight your achievements.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Product Data BI Analyst - Hybrid London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Power BI and data analysis. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Product Data Analyst position and how you can contribute to our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Collaboration Skills: Since this role involves working across teams, make sure to mention any past experiences where you’ve successfully collaborated with others. We value teamwork, so let us know how you can bring that spirit to StudySmarter!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be one step closer to joining our awesome team in London!
How to prepare for a job interview at Wilmington plc
✨Know Your Power BI Inside Out
Make sure you’re well-versed in Power BI. Brush up on your skills by creating sample dashboards or reports that showcase your ability to turn data into insights. Be ready to discuss specific projects where you've used Power BI effectively.
✨Understand the Insurance Market
Familiarise yourself with the insurance industry and its data needs. Research current trends and challenges in the market, so you can speak knowledgeably about how your role as a Product Data Analyst can contribute to innovative solutions.
✨Prepare for Collaborative Scenarios
Since collaboration is key in this role, think of examples where you’ve worked across teams. Prepare to discuss how you’ve communicated complex data findings to non-technical stakeholders and how you’ve contributed to team projects.
✨Showcase Your Analytical Mindset
Be ready to demonstrate your strong data analysis skills. Prepare to walk through your thought process on how you approach data problems, including any methodologies or tools you use to derive insights and make data-driven decisions.