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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 Woking 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 Woking
✨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 related to graph concepts and AI. We want you to feel confident and ready to impress!
✨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 Woking
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Graph Curator role. Highlight your experience with Knowledge Graphs, data management, and any relevant technical skills. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your skills can contribute to our team. Be sure to mention your understanding of AI and data integrity – it’s key for us!
Showcase Your Attention to Detail: As a Graph Curator, attention to detail is crucial. In your application, make sure to demonstrate this skill. Whether it's through your CV formatting or the clarity of your writing, we want to see that eagle eye in action!
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 shows you’re keen on joining our team at StudySmarter!
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 fundamentals confidently will show that you understand the core of what the role entails.
✨Prioritisation is Key
Prepare to talk about how you would prioritise tasks when faced with multiple requests. Think of examples where you've had to assess urgency and business impact, as this will demonstrate your analytical skills and strategic thinking.
✨Showcase Your Attention to Detail
Be ready to provide examples of how you've spotted inconsistencies or errors in data before. Highlighting your eagle eye for detail will reassure interviewers that you can maintain the high standards required for quality validation.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You might be asked to translate technical jargon for non-technical stakeholders, so showing that you can bridge that gap will be a big plus in your interview.
