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- Tasks: Apply advanced data science techniques to real estate modelling and analysis.
- Company: Join Knight Frank Group, a leading name in the real estate industry.
- Benefits: Enjoy a competitive salary and the chance to work in a vibrant London office.
- Other info: Collaborate with stakeholders and enhance your career in a 6-month contract.
- Why this job: Make an impact by delivering high-quality analytical projects in a dynamic environment.
- Qualifications: Strong Python skills and advanced modelling experience required.
The predicted salary is between 50000 - 65000 £ per year.
Knight Frank Group is seeking an Econometrician / Data Scientist for a 6 month fixed-term contract at their Baker Street office in London. The role focuses on applying advanced econometric and data science techniques to real estate modelling and analysis.
Candidates should have a strong background in Python, along with advanced modelling experience. The role involves collaboration with stakeholders to develop analytical projects and deliver high-quality outputs. A competitive salary is offered.
Real Estate Data Scientist & Econometrician - London employer: Knight Frank Group
Contact Detail:
Knight Frank Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Real Estate Data Scientist & Econometrician - London
✨Tip Number 1
Network like a pro! Reach out to professionals in the real estate and data science fields on LinkedIn. A friendly message can open doors and lead to referrals that might just land you that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects and any econometric models you've built. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Research Knight Frank Group and their recent projects. Tailor your answers to show how your experience aligns with their needs, especially in real estate modelling.
✨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 serious about joining the team!
We think you need these skills to ace Real Estate Data Scientist & Econometrician - London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python expertise and any advanced modelling experience you have. We want to see how your skills can contribute to our real estate projects!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the specific requirements of the Econometrician/Data Scientist role. We love seeing how you connect your experience to what we do.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to understand and get straight to the point about your achievements.
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 without any hiccups!
How to prepare for a job interview at Knight Frank Group
✨Know Your Data Science Stuff
Make sure you brush up on your Python skills and econometric techniques before the interview. Be ready to discuss specific projects where you've applied these skills, as they’ll want to see how you can bring value to their real estate modelling.
✨Understand the Real Estate Market
Familiarise yourself with current trends in the real estate market, especially in London. Being able to discuss how data science can impact real estate decisions will show that you’re not just a techie but also understand the industry.
✨Prepare for Collaboration Questions
Since the role involves working with stakeholders, think of examples where you’ve successfully collaborated on projects. Highlight your communication skills and how you’ve translated complex data into actionable insights for non-technical audiences.
✨Ask Insightful Questions
Prepare some thoughtful questions about Knight Frank Group’s current analytical projects or their approach to data science in real estate. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.