Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Deliver innovative data-driven insights and analysis in real estate modelling and forecasting.
- Company: Join a leading property and research environment with a market-leading Modelling and Intelligence team.
- Benefits: Fixed-term contract with opportunities for professional growth and collaboration.
- Other info: Work in a dynamic central London office with a focus on collaboration and innovation.
- Why this job: Make an impact by applying your data science skills to solve real-world business problems.
- Qualifications: Experience in econometrics, statistics, and data science techniques is essential.
The predicted salary is between 50000 - 70000 £ per year.
Be part of a team delivering innovative data-driven insight and analysis within a leading property and research environment. An exciting opportunity has arisen for an enthusiastic and innovative Econometrician/Data Scientist to join a market-leading Modelling and Intelligence team. The successful candidate will work on research projects focused on real estate modelling, forecasting, and analytical insight generation.
The role will involve enhancing existing econometric and statistical models, while also developing new analytical projects in collaboration with stakeholders across multiple real estate sectors. This is a research-oriented position ideally suited to candidates with experience applying econometric, statistical, and data science techniques to solve commercial business problems.
Based in a central London office, the role plays a key part in delivering analytical insight and strategic intelligence to internal stakeholders and clients across an international network. Reporting to the Head of Data Science, the position is offered on a fixed-term contract basis. Candidates should be comfortable working independently while also collaborating closely with cross-functional analytics and research teams. Prior experience within the real estate sector would be advantageous, although not essential.
Operating Environment
The role sits within the Modelling and Intelligence function as part of a wider Global Research division. Day-to-day management will be provided by the Head of Data Science.
Technical Responsibilities
- Collaborate with colleagues across Data Science, Data Engineering, Geospatial, and Innovation teams to deliver econometric and data science analysis relating to real estate trends and market behaviour.
- Apply advanced statistical and econometric techniques to complex datasets.
- Strong Python capability is essential.
- Experience with Databricks and Azure DevOps is highly desirable, though not mandatory.
- Manipulate, cleanse, and analyse large proprietary and external datasets.
- Produce regular analytical outputs, dashboards, reports, and data books for internal stakeholders.
- Clearly communicate findings and insights to both technical and non-technical audiences.
Data Scientist employer: Norton Blake
Contact Detail:
Norton Blake Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to econometrics or real estate. This will give potential employers a taste of what you can do and how you can contribute to their team.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data science and real estate. We recommend practising common interview questions and even doing mock interviews with friends to build your confidence.
✨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, we love seeing candidates who are proactive and take the initiative to reach out directly.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Data Scientist role. Highlight any econometric or statistical projects you've worked on, especially those related to real estate.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how your background makes you a great fit for our Modelling and Intelligence team. Be sure to mention any relevant tools like Python or Databricks.
Showcase Your Analytical Skills: In your application, include examples of how you've applied advanced statistical techniques to solve real-world problems. We love seeing how you’ve turned data into actionable insights!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role in our central London office.
How to prepare for a job interview at Norton Blake
✨Know Your Data Science Stuff
Make sure you brush up on your econometric and statistical techniques before the interview. Be ready to discuss how you've applied these methods in past projects, especially in relation to real estate or similar sectors. This will show that you can hit the ground running!
✨Showcase Your Collaboration Skills
Since this role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated with others in previous roles. Highlight any experience you have working with data engineers or geospatial teams, as this will demonstrate your ability to work well in a team environment.
✨Prepare for Technical Questions
Expect some technical questions about Python and data manipulation. Brush up on your coding skills and be ready to solve problems on the spot. If you have experience with Databricks or Azure DevOps, make sure to mention it, as it could give you an edge over other candidates.
✨Communicate Clearly
You'll need to explain complex findings to both technical and non-technical audiences. Practice summarising your past projects and insights in a way that's easy to understand. This will show that you can effectively communicate your analytical insights to stakeholders, which is crucial for this role.