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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, knowledge graphs, and strong analytical skills.
- 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 Bristol 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 Bristol
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work with Knowledge Graphs. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or a project that highlights your understanding of graph concepts and data curation. This will give you an edge when discussing your expertise during interviews.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge. Be ready to discuss how you would handle real-world scenarios involving AI-assisted curation and data integrity.
✨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 about their job search!
We think you need these skills to ace Graph Curator in Bristol
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. Use clear examples from your past work where you’ve successfully managed data integrity or resolved complex issues.
Communicate Clearly: Remember, you’ll need to explain complex concepts to non-technical stakeholders. Use your application to show us how you can communicate effectively. Avoid jargon and keep it simple – we appreciate clarity!
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 contribute effectively.
✨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 ability to drive value.
✨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 them 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 communicate effectively will set you apart from other candidates.
