Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy graph solutions to model complex relationships across various domains.
- Company: Leading tech firm specialising in data science and innovative solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and make impactful decisions through cutting-edge data technologies.
- Qualifications: 3+ years in Data Science, expertise in Neo4j, and strong programming skills in Python.
- Other info: Collaborative environment with a focus on real-world applications and career advancement.
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: GM Analytic Software
Contact Detail:
GM Analytic Software Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Bristol
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We can’t stress enough how important it is to make connections; sometimes, it’s not just what you know, but who you know that gets you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your graph database projects and any cool data science work you've done. We love seeing practical examples of your expertise, so don’t hold back!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. We recommend practising common graph algorithms and Cypher queries. Being able to talk through your thought process will impress potential employers.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who are ready to dive into the world of data science with us.
We think you need these skills to ace Data Scientist in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with graph databases and ontologies. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data science and how your expertise in Neo4j and graph algorithms can benefit us at StudySmarter. Keep it engaging and personal!
Showcase Your Technical Skills: When filling out your application, be specific about your technical skills. Mention your proficiency in Python, experience with Docker, and any graph ML frameworks you’ve worked with. We love seeing concrete examples of your work!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at GM Analytic Software
✨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 implemented graph solutions in the past. This is your chance to showcase your technical skills!
✨Showcase Your Ontology Skills
Prepare examples of how you've designed and managed ontologies in previous roles. Think about specific projects where you unified data from various sources. Being able to articulate your thought process will impress the interviewers.
✨Demonstrate Cross-Functional Collaboration
Be ready to talk about times when you've worked with different teams to translate operational needs into data models. Highlight your communication skills and how you ensure everyone is on the same page when it comes to data integration.
✨Production Deployment Focus
Since they’re looking for someone who can move solutions from research to production, prepare to discuss your experience with CI/CD pipelines and deploying reliable systems. Share specific examples of how you've tackled challenges in production environments.
