Product Analyst
We are seeking a Product Analyst to support the delivery and continuous improvement of Computer Vision AI workflows. This role focuses on coordinating operational teams, maintaining quality standards, supporting stakeholders (including clients and internal users), and helping product teams translate requirements into clear processes and deliverables. The ideal candidate is organized, detail-oriented, and comfortable working across operations, technical teams, and end users.
Job Responsibilities
- Coordinate end-to-end data and annotation workflows across multiple sites, teams, and datasets.
- Support data quality management practices (e.g., sampling checks, multi-stage quality reviews) and track quality outcomes over time.
- Gather and clarify requirements from stakeholders; translate them into workflow steps, acceptance criteria, and documentation.
- Support issue intake and resolution: manage L1 triage, coordinate escalation, and track closure with relevant teams.
- Maintain operational documentation (SOPs, workflow guides, user manuals, release notes) to ensure consistent execution.
- Prepare regular operational and quality reporting for stakeholders; highlight risks, bottlenecks, and improvement opportunities.
- Work with ML/engineering teams to ensure annotation outputs meet agreed specifications and timelines.
- Contribute to continuous improvement initiatives (process simplification, tooling improvements, turnaround-time reduction).
Job Requirements
- Bachelor's degree in information systems, Data Analytics, Computer Science, Engineering, or a related field (or equivalent practical experience).
- 1–2 years of experience in a coordination role such as product support, operations, project coordination, data operations, or related roles.
- Experience handling customer/user support requests and coordinating resolutions is an advantage.
- Exposure to agriculture/manufacturing/industrial contexts (especially Palm Oil industries) is a strong plus
- Strong organization skills and attention to detail; able to coordinate operational workflows end-to-end.
- Strong written communication skills for documentation and stakeholder updates.
- Basic analytical ability to interpret operational metrics and identify issues or trends.
- Familiarity with Agile ways of working (e.g., managing tickets, sprints, structured handovers).
- Experience with AI/ML workflows, including datasets, annotation, or model-related deliverables.
- Experience with annotation tools (e.g., Label Studio or similar platforms).
- Experience with dashboards / reporting tools (e.g., Power BI, Tableau, Metabase) for operational reporting.
- Familiarity with quality measurement concepts (e.g., inter-annotator agreement, sampling-based QA/QC).
- Experience with product/project tools (e.g., JIRA, Confluence) and documentation practices.
- Working knowledge of SQL and/or Python for diagnostics or reporting.
- Exposure to cloud platforms (e.g., AWS)
- Google Professional Data Analytics Certification
- AWS Certified Cloud Practitioner
- Advanced SQL Certification (e.g., Oracle, Microsoft)
