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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 skill development.
- 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 growth.
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 Glasgow 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 Glasgow
✨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. This gives us something tangible to discuss during interviews.
✨Tip Number 3
Prepare for the interview by understanding our company culture and values. We love candidates who align with our mission, so do your homework!
✨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 us.
We think you need these skills to ace Graph Curator in Glasgow
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, as these are key for us.
Showcase Your Attention to Detail: As a Graph Curator, attention to detail is crucial. In your application, provide examples of how you've successfully managed complex datasets or resolved inconsistencies in the past. We love seeing 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 topics confidently will show that you understand the fundamentals of Knowledge Graphs and can engage in meaningful conversations about them.
✨Prioritisation Skills are Key
Prepare to demonstrate your analytical prioritisation skills. Think of examples where you've had to assess multiple tasks and determine which ones would drive the most business value. This will help you showcase your ability to manage inbound requests effectively.
✨Familiarise Yourself with AI/LLM
Since this role involves interacting with AI-generated data, make sure you understand how Generative AI works and its common pitfalls, like hallucinations. Being able to articulate these concepts will highlight your readiness to be the human-in-the-loop for quality validation.
✨Communicate Clearly
Practice explaining complex data modelling 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 from other candidates.
