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- Tasks: Design and deploy graph solutions to model complex relationships across various domains.
- Company: Innovative tech firm specialising in data science and graph technologies.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a cutting-edge team and make impactful decisions through data-driven insights.
- Qualifications: 3+ years in Data Science, expertise in Neo4j, and strong programming skills in Python.
- Other info: Collaborative environment with a focus on deploying reliable systems and long-term data quality.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a Data Scientist with deep expertise in Knowledge Graphs and Ontologies and the ability to work across domains. You will design and deploy production-grade graph solutions that model relationships not only between UAVs, missions, and sensors, but across company processes end-to-end: from operations and production to HR and delivery. Your work will provide a transversal view of how data and processes interconnect, powering insights and decision-making across the organization.
Key Responsibilities
- Ontology Design & Management: Design and maintain scalable ontologies to unify mission data, sensor outputs, flight logs, and operational parameters.
- Graph Engineering (Neo4j): Implement, optimize, and operate Neo4j schemas; write high-performance Cypher queries and ensure production scalability.
- Graph Data Science: Apply graph algorithms (e.g., centrality, pathfinding, community detection) and graph ML to derive actionable insights.
- Production Deployment: Move solutions from research to production (TRL > 6); integrate graph models into APIs and pipelines with reliability and latency constraints.
- Data Integration: Build ingestion pipelines for structured and unstructured data into the Knowledge Graph.
- Cross-Functional Collaboration: Translate operational and domain requirements into robust data and graph models.
Requirements
- Technical Skills
- Graph Databases: Advanced Neo4j expertise, including architecture, drivers, administration, and Cypher.
- Ontology & Semantics: Strong experience with data modeling, ontologies, and semantic technologies (RDF, OWL, SPARQL).
- Programming: High proficiency in Python (pandas, networkx, py2neo, neo4j-driver).
- Graph ML: Experience with Neo4j GDS or frameworks such as PyTorch Geometric or DGL.
- Production Engineering: Hands-on experience with Docker, REST APIs (FastAPI/Flask), and CI/CD pipelines.
- Core Data Science Profile
- 3+ years of experience in Data Science or Data Engineering.
- Experience with NLP for entity and relationship extraction is a plus.
- Strongly skilled in standard ML workflows (Scikit-Learn, XGBoost).
- Experience with geospatial data (GIS, GeoPandas) is valued.
Education
- MSc in Computer Science, Data Science, or a related engineering field (PhD welcome, but practical delivery is prioritized).
Profile We're Looking For
- Production Builder: You focus on deploying reliable systems, not just experiments.
- Versatile Specialist: Deep in graph technologies, comfortable across the full data stack when needed.
- Structured Thinker: You value strong data models, data quality, and long-term maintainability.
Data Scientist in Bristol employer: TEKEVER Ltd
Contact Detail:
TEKEVER Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Bristol
✨Tip Number 1
Network like a pro! Attend industry meetups, webinars, or conferences related to data science and graph technologies. You never know who you might bump into that could lead you to your dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Neo4j and graph algorithms. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each role by highlighting relevant experience in ontology design and production deployment. Make it clear how your skills align with their needs.
✨Tip Number 4
Use our website to apply! We’ve got a streamlined process that makes it easy for you to showcase your expertise in data science and graph technologies. Let’s get you that job!
We think you need these skills to ace Data Scientist in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Scientist. Highlight your experience with graph databases, Neo4j, and any relevant projects that showcase your skills in ontology design and management.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how your expertise aligns with our needs. Mention specific examples of how you've applied graph algorithms or worked on production-grade solutions.
Showcase Your Technical Skills: Don’t just list your skills; demonstrate them! Include links to projects or GitHub repositories where we can see your work with Python, Cypher queries, and any graph ML frameworks you've used.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at TEKEVER Ltd
✨Know Your Graphs
Make sure you brush up on your knowledge of graph databases, especially Neo4j. Be ready to discuss your experience with Cypher queries and how you've optimised schemas in past projects. This will show that you’re not just familiar with the technology but can also apply it effectively.
✨Showcase Your Ontology Skills
Prepare examples of how you've designed and managed ontologies in previous roles. Discuss specific challenges you faced and how you overcame them. This will demonstrate your ability to unify complex data sets and highlight your problem-solving skills.
✨Demonstrate Cross-Functional Collaboration
Think of instances where you've worked with different teams to translate operational requirements into data models. Be ready to explain how you communicated technical concepts to non-technical stakeholders, as this is crucial for the role.
✨Production Deployment Experience
Be prepared to talk about your experience moving solutions from research to production. Highlight any work you've done with Docker, REST APIs, or CI/CD pipelines. This will show that you understand the importance of reliability and scalability in production environments.
