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- Tasks: Develop predictive models to forecast property trends and customer behaviour.
- Company: Join a fast-growing start-up in the innovative PropTech sector.
- Benefits: Enjoy hybrid working, clear career progression, and a collaborative culture.
- Why this job: Make a real impact in the property industry with AI/ML-driven projects.
- Qualifications: 3+ years in Data Science or Machine Learning; strong Python and SQL skills required.
- Other info: Work closely with cross-functional teams to drive innovation and insights.
The predicted salary is between 51000 - 85000 £ per year.
Paying up to £85,000 + bonus
Hybrid in London
AI/ML-Driven PropTech
I am currently working with a start/scale up within the PropTech sector looking to hire a Data Scientist to work on high-impact predictive modelling projects in a fast-growing company. This role offers the opportunity to work end-to-end on ML models, helping to revolutionise the property industry by leveraging data-driven insights.
As a Data Scientist, you’ll be building and optimising predictive models to understand trends in the property market, such as likelihood of sale and customer retention. You’ll work closely with Data Engineers and Product teams to drive AI/ML innovation while ensuring models are scalable and impactful.
What You’ll Be Doing:
- Developing predictive models to forecast property trends and customer behaviour.
- Leveraging MLOps best practices to ensure efficient model deployment and monitoring.
- Working end-to-end across the data pipeline – from data extraction to model evaluation.
- Collaborating with cross-functional teams to turn insights into actionable business decisions.
Tech Stack & requirements:
- Python | SQL | Snowflake | DBT | Tableau | Dataiku
- 3+ years of experience in Data Science or Machine Learning.
- Strong Python & SQL skills, with experience working in cloud-based data environments.
- A problem-solver with a commercial mindset who can translate data insights into business impact.
Why Join?
- Fast-growing company with exciting AI/ML-driven initiatives.
- Clear career progression – structured frameworks for growth.
- Hybrid working – flexibility with 2-3 days per week in London HQ.
- Be part of a collaborative and innovative culture where your work directly impacts the business.
If you’re interested in this role, apply through the AD to find out more!
Senior Data Scientist (London Area) employer: La Fosse
Contact Detail:
La Fosse Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (London Area)
✨Tip Number 1
Familiarise yourself with the specific tech stack mentioned in the job description. Brush up on your Python and SQL skills, and consider working on projects that involve Snowflake, DBT, or Tableau to showcase your hands-on experience.
✨Tip Number 2
Highlight any previous experience you have with predictive modelling and MLOps best practices. Be prepared to discuss specific projects where you've successfully deployed models and how they impacted business decisions.
✨Tip Number 3
Network with professionals in the PropTech sector or attend relevant meetups and conferences. This can help you gain insights into industry trends and potentially connect you with someone at the company.
✨Tip Number 4
Prepare for technical interviews by practising common data science problems and case studies. Focus on how to communicate your thought process clearly, as collaboration with cross-functional teams is key in this role.
We think you need these skills to ace Senior Data Scientist (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Data Science and Machine Learning. Emphasise your skills in Python, SQL, and any cloud-based data environments you've worked with, as these are crucial for the role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the PropTech sector and your understanding of AI/ML applications. Mention specific projects or experiences that demonstrate your ability to develop predictive models and collaborate with cross-functional teams.
Showcase Your Projects: If you have worked on relevant projects, consider including a portfolio or links to your work. Highlight any predictive modelling projects that had a significant impact, especially those that involved MLOps best practices.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail during the application process. Brush up on your knowledge of the tech stack mentioned in the job description, particularly Python, SQL, and tools like Tableau and Dataiku.
How to prepare for a job interview at La Fosse
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python and SQL during the interview. Be prepared to discuss specific projects where you've used these skills, especially in cloud-based environments, as this is crucial for the role.
✨Demonstrate Your Problem-Solving Ability
Prepare examples of how you've tackled complex data challenges in the past. Companies are looking for candidates who can translate data insights into actionable business strategies, so be ready to discuss your thought process.
✨Familiarise Yourself with MLOps Practices
Since the role involves leveraging MLOps best practices, brush up on your knowledge of model deployment and monitoring. Being able to discuss how you ensure models are scalable and impactful will set you apart.
✨Understand the PropTech Landscape
Research the property technology sector and current trends. Showing that you understand the market dynamics and can apply your data science skills to forecast property trends will demonstrate your genuine interest in the role.
