Job description
The AI Information Scientist at Private Advertiser assumes ownership of a strategic data problem: turning complex data into trusted, governed information assets. This is not a traditional data engineering role. It sits at the intersection of data governance, AI research, and business enablement, with an emphasis on responsible AI and data quality. You will influence how data flows, how metadata is captured, and how AI-ready information is discovered and consumed by teams across the organization. You will collaborate with data scientists, product teams, compliance, and IT to design information architectures that scale with AI initiatives and regulatory requirements.
As part of our data-driven culture, you will define metadata models, lineage, and quality rules, champion data literacy, and implement governance controls that balance innovation with privacy and security. Your work will enable AI systems—from knowledge graphs to NLP pipelines—to leverage accurate, timely, and compliant information. This role blends strategic thinking with practical delivery: translating business problems into AI information requirements, defining success metrics, and building reusable data governance patterns that accelerate time-to-insight for stakeholders.
Private Advertiser offers a collaborative environment in which data professionals partner with cross-functional teams to push the boundaries of AI-enabled decision making while maintaining a strong emphasis on data stewardship and governance. If you are passionate about shaping how information is used to power intelligent products and responsible AI, we want to hear from you.
Responsibility
- Lead design and governance of AI-ready information assets across data lifecycles, ensuring proper metadata, lineage, and quality controls.
- Collaborate with data scientists, engineers, and business stakeholders to translate business problems into AI information requirements and specifications.
- Define and maintain metadata models, data catalogs, data lineage, privacy considerations, and governance workflows.
- Architect scalable information schemas, ontologies, and data models to support AI use cases including knowledge graphs, embeddings, and NLP datasets.
- Evaluate, monitor, and operationalize AI/ML models with governance controls and risk mitigation strategies.
- Implement data security, privacy, and compliance controls; enforce data access policies aligned with regulatory requirements.
- Drive data literacy, governance practices, and documentation; promote best practices across analytics teams.
- Lead data stewardship initiatives and partner with stakeholders to ensure data quality and trust across AI initiatives.
Qualification
- Bachelor's or Master’s degree in Computer Science, Data Science, AI, Statistics, or a related field.
- 5+ years of experience in data governance, information management, or AI-focused data engineering.
- Strong knowledge of data catalogs, metadata management, data lineage, data quality frameworks, and privacy/compliance (e.g., PDPA).
- Hands-on experience with AI/ML lifecycle, model governance, MLOps, and responsible AI practices.
- Proficiency in SQL and Python; experience with data modeling, knowledge graphs, and NLP techniques.
- Excellent stakeholder management, communication, and collaboration skills; ability to translate technical concepts for non-technical audiences.
- Experience with cloud data platforms (AWS/GCP/Azure) and data tooling (dbt, Airflow, Kafka) is a plus.