Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Curate and manage a Knowledge Graph, ensuring data accuracy and relevance.
- Company: Join a forward-thinking tech company focused on AI and data integrity.
- Benefits: Flexible remote work, competitive pay, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and make a real impact on data quality.
- Qualifications: Experience with Knowledge Graphs, data management, and strong analytical skills.
- Other info: Dynamic role with potential for contract extension and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for a detail-oriented and strategic Knowledge Graph Curator. In this role, you will sit at the intersection of AI automation and human judgment. You will not only manage incoming requests from partner teams but also proactively shape the growth of our Knowledge Graph (KG) to ensure high fidelity, relevance, and connectivity. You will serve as the expert human-in-the-loop, validating LLM-generated entities and ensuring our graph represents the "ground truth" for the business.
What You'll Do
- Pipeline Management & Prioritization
- Manage Inbound Requests: Act as the primary point of contact for partner teams (Product, Engineering, Analytics) requesting new entities or schema changes.
- Strategic Prioritization: Triage the backlog of requests by assessing business impact, urgency, and technical feasibility.
- AI-Assisted Curation & Human-in-the-Loop Automation
- Interact with internal tooling to review entities generated by Large Language Models (LLMs). You will approve high-confidence data, edit near-misses, and reject hallucinations.
- Quality Validation: Perform rigorous QA on batches of generated entities to ensure they adhere to the strict ontological standards and factual accuracy required by the KG.
- Model Feedback Loops: Participate in ad-hoc labeling exercises (creation of Golden Sets) to measure current model quality and provide training data to fine-tune classifiers and extraction algorithms.
- Data Integrity & Stakeholder Management
- Manual Curation & Debugging: Investigate bug reports from downstream users or automated anomaly detection systems. You will manually fix data errors, merge duplicate entities, and resolve conflicting relationships.
- Feedback & Reporting: Close the loop with partner teams. You will report on the status of their requests, explain why certain modeling decisions were made, and educate stakeholders on how to best query the new data.
Required Skills
- Technical & Domain Expertise
- Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, Properties).
- Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities.
- Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus.
- AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground-truth data in training.
- Operational & Soft Skills
- Analytical Prioritization: Ability to look at a list of 50 tasks and determine the 5 that will drive the most business value.
- Attention to Detail: An "eagle eye" for spotting inconsistencies, typos, and logical fallacies in data.
- Stakeholder Communication: Ability to translate complex data modeling concepts into clear language for non-technical product managers and business stakeholders.
- Tool Proficiency: Comfort learning proprietary internal tools, ticketing systems (e.g., Jira), and spreadsheet manipulation (Excel/Google Sheets).
Graph Curator in Dartford employer: HireTalent - Staffing & Recruiting Firm
Contact Detail:
HireTalent - Staffing & Recruiting Firm Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graph Curator in Dartford
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or a personal project that highlights your expertise in Knowledge Graphs. It’s a great way to demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to graph curation. We want you to feel confident and ready to showcase your knowledge!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Graph Curator in Dartford
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Graph Curator role. Highlight your experience with Knowledge Graphs, data management, and any relevant tools like SQL or SPARQL. We want to see how your skills align with what we’re looking for!
Showcase Your Attention to Detail: Since this role requires an eagle eye for spotting inconsistencies, be sure to demonstrate your attention to detail in your application. Whether it’s through a well-structured CV or a meticulously crafted cover letter, let us see that you can catch the small stuff!
Communicate Clearly: We value clear communication, especially when it comes to complex concepts. Use straightforward language in your application to explain your past experiences and how they relate to the role. This will show us that you can translate technical jargon into something everyone can understand.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the position. Plus, it makes the whole process smoother for both of us!
How to prepare for a job interview at HireTalent - Staffing & Recruiting Firm
✨Know Your Graphs
Make sure you brush up on your knowledge of graph concepts, including nodes, edges, and properties. Being able to discuss these topics confidently will show that you understand the fundamentals of Knowledge Graphs and can contribute effectively.
✨Prioritisation is Key
Prepare to talk about how you would prioritise tasks in a busy environment. Think of examples where you've had to assess urgency and business impact, as this role requires strong analytical prioritisation skills.
✨Showcase Your Attention to Detail
Be ready to demonstrate your eagle eye for spotting inconsistencies or errors in data. You might be asked to review a sample dataset, so practice explaining your thought process when identifying issues.
✨Communicate Clearly
Since you'll need to explain complex data concepts to non-technical stakeholders, practice simplifying technical jargon into layman's terms. This will help you stand out as someone who can bridge the gap between technical and non-technical teams.
