Data Science Manager – Property Tech – London
UK | High Growth B2B SaaS | Hands On Data Science Manager
I am working with a scaling UK PropTech business where Machine Learning and AI sit at the core of the product and commercial strategy.
They are hiring a hands on Data Science Manager who can lead their Data team while remaining technically involved in modelling, production machine learning and shaping the overall AWS based data platform.
This is not a pure management role. They are looking for a strong Data Scientist first, someone comfortable across the full lifecycle from ingestion and feature engineering through to modelling and deployment.
Their data estate has evolved over time and is currently spread across multiple siloed systems with differing structures and standards. The platform is built on AWS, but architectural consistency is lacking. They need someone who understands what good looks like in a modern cloud native environment, can rationalise fragmented systems, and proactively define a clear data and AI roadmap. You will lead a Data team of 5-6 across Data Science and Data Engineering, raising standards while still contributing directly to predictive models and AI driven tools. This is a genuine opportunity to bring structure, clarity and technical direction to a business where data is fundamental to competitive advantage.
Key areas of focus include:
• Designing and improving a scalable AWS data platform
• Creating architectural coherence across siloed systems
• Leading end to end machine learning from feature engineering through to production deployment
• Embedding robust MLOps and model performance monitoring
• Improving ingestion, transformation and production readiness of data
• Defining and owning a multi year data and AI roadmap aligned to business growth
They are looking for someone who:
• Has strong hands on Data Science capability
• Has deployed machine learning models into production, not just experimentation
• Is comfortable operating across data engineering and architecture discussions
• Has worked within messy, multi system, inconsistent data environments
• Brings architectural thinking, even if not formally titled Head of Architecture
• Has experience leading and developing a small, high impact team
• Is proactive, commercially aware and confident setting technical direction
This is less about hiring a traditional enterprise Data Engineering leader and more about finding a technically credible, AI centric builder who can combine modelling depth, engineering awareness and leadership.
Salary: £90,000 to £100,000 plus significant equity.
Location: London – Hybrid working 2 to 3 days in the office when needed, with a flexible and pragmatic approach.
This is an opportunity to shape a modern, AI driven data capability on AWS within a scaling SaaS business where data underpins product differentiation. You will have genuine ownership, leadership visibility and meaningful equity upside.
If you are a technically strong Data Science leader who enjoys solving architectural complexity and building high performing teams, please APPLY NOW.
UK | High Growth B2B SaaS | Hands On Data Science Manager
I am working with a scaling UK PropTech business where Machine Learning and AI sit at the core of the product and commercial strategy.
They are hiring a hands on Data Science Manager who can lead their Data team while remaining technically involved in modelling, production machine learning and shaping the overall AWS based data platform.
This is not a pure management role. They are looking for a strong Data Scientist first, someone comfortable across the full lifecycle from ingestion and feature engineering through to modelling and deployment.
Their data estate has evolved over time and is currently spread across multiple siloed systems with differing structures and standards. The platform is built on AWS, but architectural consistency is lacking. They need someone who understands what good looks like in a modern cloud native environment, can rationalise fragmented systems, and proactively define a clear data and AI roadmap. You will lead a Data team of 5-6 across Data Science and Data Engineering, raising standards while still contributing directly to predictive models and AI driven tools. This is a genuine opportunity to bring structure, clarity and technical direction to a business where data is fundamental to competitive advantage.
Key areas of focus include:
• Designing and improving a scalable AWS data platform
• Creating architectural coherence across siloed systems
• Leading end to end machine learning from feature engineering through to production deployment
• Embedding robust MLOps and model performance monitoring
• Improving ingestion, transformation and production readiness of data
• Defining and owning a multi year data and AI roadmap aligned to business growth
They are looking for someone who:
• Has strong hands on Data Science capability
• Has deployed machine learning models into production, not just experimentation
• Is comfortable operating across data engineering and architecture discussions
• Has worked within messy, multi system, inconsistent data environments
• Brings architectural thinking, even if not formally titled Head of Architecture
• Has experience leading and developing a small, high impact team
• Is proactive, commercially aware and confident setting technical direction
This is less about hiring a traditional enterprise Data Engineering leader and more about finding a technically credible, AI centric builder who can combine modelling depth, engineering awareness and leadership.
Salary: £90,000 to £100,000 plus significant equity.
Location: London – Hybrid working 2 to 3 days in the office when needed, with a flexible and pragmatic approach.
This is an opportunity to shape a modern, AI driven data capability on AWS within a scaling SaaS business where data underpins product differentiation. You will have genuine ownership, leadership visibility and meaningful equity upside.
If you are a technically strong Data Science leader who enjoys solving architectural complexity and building high performing teams, please APPLY NOW.
