Knowledge Graph Operations Lead, Ads Content Understanding
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Job Description
Knowledge Graph Operations Lead managing a team of KG experts at Reddit. Overseeing operations and collaborating closely with ML teams to support Ads Business.
Responsibilities:
- Lead, mentor, and unblock a dedicated pod of Knowledge Graph experts, managing their workload and task assignments.
- Prioritize and manage all incoming requests from sister teams.
- Coordinate the team's daily work, ensuring efficient and high-quality expansion of the Knowledge Graph.
- Develop and manage the onboarding and training process for new KG experts, ensuring they ramp up effectively.
- Define, design, and maintain key performance indicators (KPIs) and metrics for KG expansion, data quality, and team velocity.
- Track and communicate team execution and progress against predefined KPIs to stakeholders and leadership.
- Proactively identify opportunities to optimize processes, increase team velocity, and improve data quality metrics.
- Identify and document gaps in current tooling and create clear feature requests for the ACI engineering team to address.
- Serve as the primary operational point of contact and collaborate closely with ML Engineers and Engineering Managers on KG-related projects.
- Contribute as a hands-on KG expert by following the established daily routine to introduce new entities into the Knowledge Graph.
- Ensure all KG work aligns with and contributes to the broader strategic goals of the Reddit Ads Business.
Requirements:
- 2+ years of experience in data operations, data curation, knowledge management, or a related field.
- Experience with at least one general programming language such as Ruby or Python
- Direct experience working with Knowledge Graphs, ontologies, taxonomies, or large-scale structured datasets.
- Strong project management skills: Proven ability to manage a backlog, prioritize competing requests, and unblock a team.
- Data-driven mindset: Experience defining, tracking, and reporting on operational metrics and KPIs.
- Excellent communication and collaboration skills, with the ability to work effectively across technical and non-technical teams.
- Familiarity with algorithms and data structures, and the ability to apply them to solve complex problems.
- A willingness to learn and stay up-to-date with SOTA ML technologies and best practices in the field.
- Nice to have:
- Experience with data-querying languages (e.g., SQL, SPARQL).
- Familiarity with the digital advertising or ad-tech landscape.
- Experience working closely with Machine Learning or Data Science teams.
- Experience in process optimization or operations management.
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