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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 technology and make a real impact on data quality.
- Qualifications: Experience with data management, strong analytical skills, and familiarity with AI concepts.
- 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 Exeter 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 Exeter
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or a personal project that highlights your expertise in Knowledge Graphs. This not only demonstrates your capabilities but also gives you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for those interviews! Research common questions related to graph curation and AI, and practice your responses. We recommend using the STAR method (Situation, Task, Action, Result) to structure your answers effectively.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Graph Curator in Exeter
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 the role and how your background makes you a perfect fit. Don’t forget to mention your attention to detail and analytical prioritisation skills – they’re key for us!
Showcase Relevant Projects: If you've worked on projects involving knowledge graphs, data curation, or AI, make sure to include them in your application. We love seeing real-world examples of your work and how you’ve tackled challenges in the past.
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 don’t miss out on any important updates. Plus, we love seeing candidates who take that extra step!
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 a long list of requests. Think of examples from your past experiences where you had to assess urgency and business impact, as this will demonstrate your analytical skills.
✨Familiarity with AI/LLMs
Get comfortable discussing generative AI and its common pitfalls, like hallucinations. Showing that you understand the importance of ground-truth data will highlight your readiness for the human-in-the-loop aspect of the job.
✨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 effectively will set you apart.
