At a Glance
- Tasks: Develop intelligent data systems for classification, enrichment, and semantic search in construction.
- Company: Join Depixen, a pioneering tech company transforming the construction industry with innovative data solutions.
- Benefits: Remote work, competitive salary, and opportunities for professional growth in a cutting-edge field.
- Other info: Collaborative environment focused on building explainable AI systems in a complex industry.
- Why this job: Make a real impact by turning fragmented data into reliable decision intelligence for the construction sector.
- Qualifications: Bachelor's degree and 4+ years in data science or related fields; strong Python skills required.
The predicted salary is between 60000 - 80000 £ per year.
About Depixen
Depixen is a London-based technology company building the digital decision infrastructure of the construction industry. As a corporate member of the World Wide Web Consortium — W3C, Depixen develops Linked Data architectures, domain-specific taxonomies, ontologies, RDF-based data structures, and knowledge graph infrastructures for construction, architecture, and building products. We work with fragmented and highly contextual industry data: product catalogues, technical documents, standards, materials, suppliers, projects, events, images, and user interactions.
About the Role
We are looking for a Senior Data Scientist to help build intelligent data systems for classification, enrichment, entity resolution, semantic search, recommendation, and knowledge graph-connected AI applications. This is not a conventional data science role. You will work at the intersection of machine learning, semantic data modelling, information retrieval, knowledge graphs, and real-world construction product data. Your work will help turn fragmented industry data into reliable, contextual, and explainable decision intelligence.
Responsibilities
- Develop machine learning and data science systems for classification, extraction, enrichment, matching, recommendation, and semantic search.
- Work with structured, semi-structured, unstructured, and graph-connected data.
- Build entity extraction, entity resolution, deduplication, and similarity-matching workflows.
- Connect AI outputs with taxonomy, ontology, RDF, and knowledge graph layers.
- Design evaluation, benchmarking, validation, and error-analysis processes.
- Improve data quality, consistency, explainability, provenance, and semantic alignment.
- Collaborate with engineering, product, and domain teams to turn business requirements into scalable technical systems.
- Support the development of production-grade semantic AI and decision-support systems.
Required Qualifications
- Bachelor’s degree in Computer Science, Data Science, AI, Software Engineering, Mathematics, Statistics, or a related field.
- 4+ years of hands-on experience in data science, machine learning, information retrieval, NLP, knowledge graphs, or related AI/data fields.
- Strong Python skills.
- Experience developing, testing, deploying, and monitoring data science or machine learning models.
- Experience with structured, semi-structured, and unstructured data.
- Practical experience in several of the following areas:
- classification
- entity extraction
- entity resolution
- semantic enrichment
- recommendation systems
- semantic search
- information retrieval
- NLP
- data quality automation
- Strong understanding of data modelling, metadata, data quality, model evaluation, benchmarking, and error analysis.
- Ability to document technical work clearly and communicate across technical and non-technical teams.
- Interest in semantic web technologies, knowledge graphs, ontologies, taxonomies, or linked data.
Preferred Qualifications
- Master’s or PhD in Computer Science, AI, Data Science, Machine Learning, NLP, Semantic Web, Knowledge Graphs, or a related field.
- Experience with RDF, OWL, SPARQL, SHACL, SKOS, JSON-LD, schema.org, ontologies, taxonomies, or Linked Data.
- Experience with graph databases or triple stores such as GraphDB, Stardog, Neo4j, Amazon Neptune, or Blazegraph.
- Experience with embeddings, vector databases, RAG, LLM-based enrichment, or knowledge graph completion.
- Experience with MLOps tools such as Docker, Kubernetes, MLflow, Weights & Biases, Airflow, or similar.
- Experience with AWS, GCP, or Azure.
- Experience in construction, architecture, BIM, building materials, technical product data, catalogues, standards, or compliance-heavy data systems.
- Contributions to open-source projects, academic publications, or applied research are a plus.
Problem Areas
You may work on: construction product classification and enrichment; entity resolution for products, suppliers, events, venues, organizations, and technical concepts; semantic search and recommendation systems; extraction of structured data from catalogues, PDFs, websites, and technical documents; knowledge graph-connected AI workflows; data quality, explainability, provenance, and validation systems.
Why This Role Is Different
Construction data cannot be understood through statistical patterns alone. The meaning of a product, material, document, technical value, supplier, or project depends on its relationship to standards, classifications, specifications, and domain knowledge. At Depixen, data science outputs are not isolated predictions. They are connected to verified data, semantic classification, ontology, RDF, and knowledge graph layers. This role is about building reliable, contextual, explainable, and machine-interpretable AI systems for one of the world’s most complex industries.
Data Science Data Science Senior Data Scientist (Remote) in London employer: Depixen
Depixen is an exceptional employer that fosters a collaborative and innovative work culture, where employees are empowered to tackle complex challenges in the construction industry through cutting-edge technology. With a strong focus on professional growth, team members have access to continuous learning opportunities and the chance to contribute to meaningful projects that shape the future of digital decision-making. Located in London, Depixen offers a dynamic environment that values creativity and encourages the exploration of semantic AI and knowledge graphs, making it an ideal place for passionate data scientists to thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Data Science Senior Data Scientist (Remote) in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Depixen. Use LinkedIn to connect and engage with their posts. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to data science and machine learning. Highlight any work with knowledge graphs or semantic AI. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on relevant topics. Be ready to discuss your experience with entity extraction, semantic search, and data quality. We want to see how you think and solve problems, so practice articulating your thought process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Depixen. Let’s make it happen!
We think you need these skills to ace Data Science Data Science Senior Data Scientist (Remote) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior Data Scientist. Highlight your experience with machine learning, semantic data modelling, and knowledge graphs. We want to see how your skills align with our needs!
Showcase Your Projects:Include specific projects that demonstrate your hands-on experience in data science and AI. If you've worked on classification systems or knowledge graph applications, let us know! This helps us see your practical skills in action.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use straightforward language to explain your technical work and how it relates to the role. We appreciate clarity, especially when communicating complex ideas!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Depixen
✨Know Your Data Science Fundamentals
Make sure you brush up on your data science fundamentals, especially in areas like machine learning, NLP, and knowledge graphs. Be ready to discuss your hands-on experience with structured, semi-structured, and unstructured data, as well as your familiarity with Python and relevant libraries.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data problems in the past. Think about projects where you developed classification systems or worked on entity resolution. Highlight your approach to improving data quality and explainability, as these are key for the role.
✨Understand the Construction Industry Context
Since this role is unique to the construction industry, do some research on how data science applies specifically to construction products and decision-making. Familiarise yourself with terms like taxonomies, ontologies, and RDF, and be ready to discuss how they relate to your work.
✨Communicate Clearly Across Teams
This position requires collaboration with both technical and non-technical teams. Practice explaining your technical work in simple terms, and think about how you can demonstrate your ability to document processes clearly. Good communication will set you apart!
