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- Tasks: Join a dynamic team to deliver innovative data-driven insights in real estate.
- Company: Leading property and research firm with a focus on collaboration.
- Benefits: Fixed-term contract with opportunities for professional growth and development.
- Other info: Work in a vibrant London office with a supportive team environment.
- Why this job: Make an impact by applying your analytical skills to real-world challenges.
- Qualifications: Degree in a quantitative field and strong experience in econometrics and statistics.
The predicted salary is between 45000 - 55000 £ 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 EnvironmentThe 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.
- Relevant university degree in a quantitative discipline.
- Minimum of 4 years’ relevant professional experience.
- Strong econometric and statistical modelling expertise.
- Excellent analytical and problem-solving skills.
- High attention to detail and accuracy in data analysis and reporting.
- Experience or understanding of the real estate sector desirable.
- Strong interpersonal and communication skills suited to a collaborative professional environment.
- Self-motivated with the ability to independently manage projects and deadlines.
Statistician in City of London employer: Norton Blake
Contact Detail:
Norton Blake Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Statistician in City of London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend events, join online forums, or even reach out to alumni from your university. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with potential employers, make sure to highlight your experience with econometric and statistical modelling. Share specific examples of how you've tackled complex datasets and delivered insights that made a difference.
✨Tailor Your Approach
Every job is unique, so don’t be afraid to tweak your pitch for each opportunity. Research the company and its projects, and align your skills with what they need. This shows you're genuinely interested and ready to contribute.
✨Apply Through Our Website
We’ve got some fantastic opportunities waiting for you on our website. Don’t miss out—apply directly through us to ensure your application gets the attention it deserves!
We think you need these skills to ace Statistician in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with econometric and statistical modelling. 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 this opportunity and how your background in data science can contribute to our Modelling and Intelligence team. Keep it engaging and personal!
Showcase Your Technical Skills: Since strong Python capability is essential, make sure to mention any relevant projects or experiences where you've used Python or other statistical techniques. We love seeing practical examples of your work!
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 role. Plus, it’s super easy!
How to prepare for a job interview at Norton Blake
✨Know Your Numbers
Brush up on your econometric and statistical modelling techniques. Be ready to discuss specific projects where you've applied these skills, especially in real estate or similar sectors. This shows you can translate theory into practice.
✨Showcase Your Python Skills
Since strong Python capability is essential, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common data manipulation tasks and be ready to explain your thought process.
✨Communicate Clearly
You’ll need to convey complex findings to both technical and non-technical audiences. Practice summarising your past projects in simple terms, focusing on the insights and impact rather than just the technical details.
✨Collaborative Mindset
Highlight your experience working with cross-functional teams. Prepare examples of how you’ve collaborated with others in previous roles, particularly in delivering analytical insights. This will show you’re a team player who can thrive in their environment.