AI Data Sourcing Manager

Leadingnation; Hong Kong; On-site; HKD 900,000 - 1,300,000; Full time

Job summary

Leadingnation is seeking a Data Sourcing Manager to lead end‑to‑end data collection pipelines, identifying data needs and partners to fuel AI and analytics initiatives. The role blends operations, product, and data to build a scalable data ecosystem.

You will own vendor management, ensure data quality, and implement governance standards while collaborating with product, AI research, and engineering teams to meet model training requirements.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Operations, Business, or related field.
• 5+ years of experience in data operations, sourcing, project management, or vendor management within a tech or AI-driven environment.
• Demonstrated ability to own cross-functional programs and deliver measurable outcomes under ambiguity.
• Strong understanding of data pipelines, annotation workflows, and AI/ML data lifecycle management.
• Experience managing third-party data providers, annotation vendors, or crowdsourcing platforms.
• Excellent project management and stakeholder communication skills.
• Familiarity with privacy regulations (e.g. GDPR, CCPA) and data security compliance is a plus.

Responsibilities

• Own and operationalize the data sourcing and collection pipeline across multiple projects and data modalities (text, audio, etc).
• Identify, evaluate, and onboard data partners, suppliers, and vendors, ensuring data quality, coverage, and compliance.
• Collaborate with product, AI research, and engineering teams to define data requirements and acquisition strategies that align with model training needs.
• Build and maintain data governance standards, ensuring ethical, privacy‑compliant, and legally sound data collection practices.
• Develop metrics and dashboards to track data pipeline performance, quality, and throughput.

Job description

About the Role

We are seeking a proactive and detail‑oriented Data Sourcing Manager to lead the design, execution, and optimization of our data collection and sourcing pipeline. This role owns the full lifecycle of our data acquisition efforts—from identifying data needs and vendors, to managing quality standards, to ensuring that our datasets fuel high‑performing AI and analytics initiatives.

The ideal candidate is a hands‑on problem solver who thrives at the intersection of operations, product, and data. You’ll combine strategic thinking and operational excellence to build a sustainable, scalable data ecosystem.

Key Responsibilities

• Own and operationalize the company’s data sourcing and collection pipeline across multiple projects and data modalities (text, audio, etc).
• Identify, evaluate, and onboard data partners, suppliers, and vendors, ensuring data quality, coverage, and compliance.
• Collaborate with product, AI research, and engineering teams to define data requirements and acquisition strategies that align with model training needs.
• Build and maintain data governance standards, ensuring ethical, privacy‑compliant, and legally sound data collection practices.
• Develop metrics and dashboards to track data pipeline performance, quality, and throughput.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Operations, Business, or a related field.
• 5+ years of experience in data operations, sourcing, project management, or vendor management within a tech or AI‑driven environment.
• Demonstrated ability to own cross‑functional programs and deliver measurable outcomes under ambiguity.
• Strong understanding of data pipelines, annotation workflows, and AI/ML data lifecycle management.
• Experience managing third‑party data providers, annotation vendors, or crowdsourcing platforms.
• Excellent project management and stakeholder communication skills.
• Familiarity with privacy regulations (e.g. GDPR, CCPA) and data security compliance is a plus.

What We’re Looking For

• A self‑starter who takes ownership, sees around corners, and proactively identifies data needs before they arise.
• A builder mindset—comfortable setting up systems, processes, and partnerships from scratch.
• Someone passionate about making high‑quality data a strategic advantage in AI development.