Data Science Manager – Property Tech – London

London
6 days ago
Create job alert

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

Related Jobs

View all jobs

Data Science PhD Internship

Data Science Product Intern (PhD Level) - Tesco

Data Science Product Intern (PhD Level)

Data Science PhD Internship - Tesco

Data Science Product Intern (PhD Level) - Tesco

Data Science Product Intern (PhD Level) - Tesco

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Robotics Tools Do You Need to Know to Get a Robotics Job?

If you’re pursuing a career in robotics, it can feel like the list of tools you should learn never ends. One job advert asks for ROS, another mentions Gazebo, another wants experience with Python, Linux, C++, RobotStudio, MATLAB/Simulink, perception stacks, control frameworks, real-time OS, vision libraries — and that’s just scratching the surface. With so many frameworks, languages and platforms, it’s no wonder robotics job seekers feel overwhelmed. But here’s the honest truth most recruiters won’t say explicitly: 👉 They don’t hire you because you know every tool — they hire you because you can apply the right tools to solve real robotics problems reliably and explain your reasoning clearly. Tools matter — but only in service of outcomes. So the real question isn’t how many tools you should know, but which tools you should master and why. For most robotics roles, the answer is significantly fewer — and far more focused — than you might assume. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable, confident, and ready to contribute from day one.

What Hiring Managers Look for First in Robotics Job Applications (UK Guide)

Robotics is one of the most dynamic, interdisciplinary fields in technology — blending mechanical systems, embedded software, controls, perception (AI/vision), modelling, simulation and systems integration. Hiring managers in this space are highly selective because robotics teams need people who can solve real-world problems under constraints, work across disciplines, and deliver safe, reliable systems. And here’s the reality: hiring managers do not read every word of your CV. Like in many tech domains, they scan quickly — often forming a judgement in the first 10–20 seconds. In robotics, those first signals are especially important because the work is complex and there’s a wide range of candidate backgrounds. This guide unpacks exactly what hiring managers look for first in robotics applications and how to optimise your CV, portfolio and cover letter so you stand out in the UK market.

The Skills Gap in Robotics Jobs: What Universities Aren’t Teaching

Robotics is no longer confined to science fiction or isolated research labs. Today, robots perform critical tasks across manufacturing, healthcare, logistics, agriculture, defence, hospitality and even education. In the UK, businesses are embracing automation to improve productivity, reduce costs and tackle labour shortages. Yet despite strong interest and a growing number of university programmes in robotics, many employers report a persistent problem: graduates are not job-ready for real-world robotics roles. This is not a question of intelligence or dedication. It is a widening skills gap between what universities teach and what employers actually need in robotics jobs. In this article, we’ll explore that gap in depth — what universities do well, where their programmes often fall short, why the disconnect exists, what employers really want, and how you can bridge the divide to build a thriving career in robotics.