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- 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 innovation 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 Leeds 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 Leeds
✨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 project that highlights your knowledge of Knowledge Graphs. It’s a great way to demonstrate your expertise beyond the application.
✨Tip Number 3
Prepare for interviews by practising common questions related to graph concepts and AI. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Graph Curator in Leeds
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Graph Curator role. Highlight your knowledge of graph concepts, data literacy, and any experience with AI or LLMs. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about Knowledge Graphs and how your background makes you a perfect fit for this role. Don’t forget to mention your attention to detail and analytical skills!
Showcase Relevant Projects: If you've worked on projects involving data curation, graph management, or AI, make sure to include them in your application. We love seeing real-world examples of your expertise and how you’ve tackled similar challenges before.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the StudySmarter team!
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 from day one.
✨Prioritisation is Key
Prepare to talk about how you would prioritise tasks when faced with a long list of requests. Think of examples where you've had to assess business impact and urgency, and be ready to explain your thought process. This will demonstrate your analytical skills and ability to drive value.
✨Showcase Your Attention to Detail
Since this role requires an eagle eye for spotting inconsistencies, come prepared with examples of how you've caught errors in data or processes in the past. Highlighting your meticulous nature will reassure them that you can maintain high standards in data integrity.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You might be asked to translate technical jargon for non-technical stakeholders, so being able to communicate clearly and effectively will set you apart. Consider role-playing with a friend to refine your explanations.
