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.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovative AI solutions.
- Why this job: Make a real impact by turning fragmented data into reliable decision intelligence.
- Qualifications: Bachelor’s degree and 4+ years in data science or related fields 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 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. Working remotely from London, you will enjoy the flexibility of a modern workplace while being part of a forward-thinking company that values creativity and expertise in data science.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Data Science Data Scientist (Remote) in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data science and machine learning. Use GitHub to share your code and demonstrate your expertise in semantic AI and knowledge graphs.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the specific challenges in the construction industry. Be ready to discuss how your experience aligns with the role at Depixen and how you can contribute to their mission.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Depixen and making an impact in the construction tech space.
We think you need these skills to ace Data Science Data Science 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 entity resolution, let us know! We love seeing real-world applications of your skills.
Be Clear and Concise:When writing your application, keep it clear and concise. Use straightforward language to explain your technical work and how it relates to the role. Remember, we appreciate good communication across both technical and non-technical teams!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss any important updates. Plus, it’s super easy!
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 discuss specific projects where you've tackled complex data challenges. Highlight how you approached problems like entity resolution or semantic enrichment, and be ready to explain your thought process and the impact of your solutions.
✨Understand the Construction Industry Context
Since this role is focused on the construction industry, it’s crucial to understand the unique challenges and data types involved. Familiarise yourself with terms like BIM, technical product data, and compliance-heavy systems to demonstrate your interest and relevance.
✨Communicate Clearly Across Teams
Practice explaining your technical work in simple terms, as you'll need to communicate effectively with both technical and non-technical teams. Prepare examples of how you've documented your work or collaborated with others to turn business requirements into technical solutions.
