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- Tasks: Analyse data and create insightful reports for residential valuations.
- Company: Leading global real estate firm with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a difference in the property sector.
- Qualifications: 2-3 years of experience in data analysis and strong technical skills.
- Other info: Exciting projects and a chance to work with diverse clients.
The predicted salary is between 36000 - 60000 £ per year.
A leading global real estate firm is seeking a skilled Data Analyst to join their residential valuations team in London. This role involves maintaining large datasets, developing SQL data models, and building Power BI dashboards.
Candidates should have 2-3 years of experience, strong technical skills, and an interest in the property sector. The ideal candidate will excel in data analysis, reporting, and client interaction, contributing to impactful insights and solutions for diverse clients.
Data Analyst: Residential Valuations & Insights employer: Jones Lang LaSalle Incorporated
Contact Detail:
Jones Lang LaSalle Incorporated Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst: Residential Valuations & Insights
✨Tip Number 1
Network like a pro! Reach out to professionals in the real estate sector on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show your interest in the property market.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL data models and Power BI dashboards. This will give potential employers a taste of what you can do and set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on common data analysis questions and scenarios. Practice explaining your thought process clearly, as client interaction is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Data Analyst: Residential Valuations & Insights
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with large datasets and SQL data models. We want to see how your skills align with the role, so don’t be shy about showcasing your technical prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re passionate about the property sector and how your background in data analysis can contribute to our team. Keep it engaging and relevant!
Showcase Your Projects: If you've worked on any projects involving Power BI dashboards or data reporting, make sure to mention them. We love seeing real examples of your work that demonstrate your analytical skills 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 this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Jones Lang LaSalle Incorporated
✨Know Your Data Inside Out
Before the interview, make sure you’re familiar with the types of datasets you might be working with. Brush up on your SQL skills and be ready to discuss how you've used data analysis in previous roles, especially in relation to residential valuations.
✨Showcase Your Technical Skills
Prepare to demonstrate your technical abilities, particularly with SQL and Power BI. You might be asked to solve a problem or create a simple dashboard on the spot, so practice these skills beforehand to show you’re up to the task.
✨Understand the Property Sector
Research the current trends in the property market and be prepared to discuss how they impact data analysis. Showing genuine interest in the sector will help you stand out as a candidate who is not just technically skilled but also passionate about the field.
✨Prepare for Client Interaction Scenarios
Since this role involves client interaction, think of examples where you've successfully communicated complex data insights to non-technical stakeholders. Be ready to explain how you can translate data into actionable insights that clients can understand and use.
