Head of Data – London – Messy Data / Web Crawlers / Data Aggregation
High Growth B2B SaaS | AI & Machine Learning Platform
£90,000 – £100,000 + Significant Equity
I am working with a scaling London based technology business where Machine Learning and AI sit at the core of the product.
The platform is built around a large-scale dataset created by crawling the web and collecting millions of listings from multiple external sources. That raw data is then structured, matched and analysed to power a suite of SaaS tools used across the market.
One of the core technical challenges is that the same entity can appear multiple times across different sources, often with slightly different attributes or descriptions. The platform uses a combination of neural networks and rule based systems to match records and build a reliable dataset over time. They are now hiring a Head of Data to take ownership of their data and AI platform.
The Opportunity
This is a hands-on leadership role where you will lead a team of 5–6 across Data Science and Data Engineering while remaining technically involved in modelling, machine learning deployment and architectural decisions.
The platform runs on AWS and includes large-scale crawlers ingesting significant volumes of external data. However, the architecture has evolved over time and data currently sits across multiple siloed systems.
They need someone who understands what good looks like in a modern data platform and can bring structure, coherence and technical direction.
You will take ownership of improving the data architecture, strengthening the matching systems and defining a clear data and AI roadmap for the business.
Key Areas of Focus
• Designing and improving a scalable AWS based data platform
• Rationalising fragmented data across multiple systems
• Leading the full machine learning lifecycle from ingestion and feature engineering through to deployment
• Improving neural network and rule based matching systems used to identify the same entities across different sources
• Embedding robust MLOps and model monitoring
• Building a coherent data architecture that supports future AI development
• Leading and developing a team of Data Scientists and Data Engineers
The Background That Works Well
Relevant experience in environments that deal with messy data from multiple external sources might include:
• Web crawling or large-scale web data ingestion
• Marketplace or data aggregation platforms
• Entity resolution, record linkage or deduplication systems
• Matching systems or recommendation engines
• Geospatial or address based data platforms
• ML systems deployed into production
You do not need sector experience, but you should be comfortable working with complex datasets where the same entity appears across multiple sources.
What They Are Looking For
• Strong Data Science background with hands on machine learning experience
• Experience deploying ML models into production environments
• Understanding of data engineering concepts and modern cloud data platforms
• Architectural thinking around data platforms and ML systems
• Experience working with messy, multi-source datasets
• Leadership experience managing small, high impact teams
• Someone proactive who can define standards and shape the data roadmap
Package
Salary: £90,000 – £100,000
Equity: Meaningful equity with real upside (3 year vesting)
Location: London – Hybrid working, typically 2–3 days in the office with a pragmatic approach to flexibility
This is a high ownership role where you will be shaping the foundations of a data and AI platform inside a scaling technology business.
If you enjoy solving complex data problems, building scalable machine learning systems and leading a small but impactful team, I would be keen to speak.
High Growth B2B SaaS | AI & Machine Learning Platform
£90,000 – £100,000 + Significant Equity
I am working with a scaling London based technology business where Machine Learning and AI sit at the core of the product.
The platform is built around a large-scale dataset created by crawling the web and collecting millions of listings from multiple external sources. That raw data is then structured, matched and analysed to power a suite of SaaS tools used across the market.
One of the core technical challenges is that the same entity can appear multiple times across different sources, often with slightly different attributes or descriptions. The platform uses a combination of neural networks and rule based systems to match records and build a reliable dataset over time. They are now hiring a Head of Data to take ownership of their data and AI platform.
The Opportunity
This is a hands-on leadership role where you will lead a team of 5–6 across Data Science and Data Engineering while remaining technically involved in modelling, machine learning deployment and architectural decisions.
The platform runs on AWS and includes large-scale crawlers ingesting significant volumes of external data. However, the architecture has evolved over time and data currently sits across multiple siloed systems.
They need someone who understands what good looks like in a modern data platform and can bring structure, coherence and technical direction.
You will take ownership of improving the data architecture, strengthening the matching systems and defining a clear data and AI roadmap for the business.
Key Areas of Focus
• Designing and improving a scalable AWS based data platform
• Rationalising fragmented data across multiple systems
• Leading the full machine learning lifecycle from ingestion and feature engineering through to deployment
• Improving neural network and rule based matching systems used to identify the same entities across different sources
• Embedding robust MLOps and model monitoring
• Building a coherent data architecture that supports future AI development
• Leading and developing a team of Data Scientists and Data Engineers
The Background That Works Well
Relevant experience in environments that deal with messy data from multiple external sources might include:
• Web crawling or large-scale web data ingestion
• Marketplace or data aggregation platforms
• Entity resolution, record linkage or deduplication systems
• Matching systems or recommendation engines
• Geospatial or address based data platforms
• ML systems deployed into production
You do not need sector experience, but you should be comfortable working with complex datasets where the same entity appears across multiple sources.
What They Are Looking For
• Strong Data Science background with hands on machine learning experience
• Experience deploying ML models into production environments
• Understanding of data engineering concepts and modern cloud data platforms
• Architectural thinking around data platforms and ML systems
• Experience working with messy, multi-source datasets
• Leadership experience managing small, high impact teams
• Someone proactive who can define standards and shape the data roadmap
Package
Salary: £90,000 – £100,000
Equity: Meaningful equity with real upside (3 year vesting)
Location: London – Hybrid working, typically 2–3 days in the office with a pragmatic approach to flexibility
This is a high ownership role where you will be shaping the foundations of a data and AI platform inside a scaling technology business.
If you enjoy solving complex data problems, building scalable machine learning systems and leading a small but impactful team, I would be keen to speak.
