Product Management - Data Insight & Analytics
Position Summary
We’re looking for a Product Manager focused on Data Insight & Analytics to lead the Samsung Apps Data Tracker and Reporting Dashboard. This role will play a key part in ensuring data accuracy, insight-driven decision‑making, and seamless reporting for Samsung project‑related initiatives.
Role and Responsibilities
- 1. Product Ownership & Strategy
- Define product vision, roadmap, and KPIs for project data tracking and reporting systems.
- Lead coordination between engineering, DevOps, and compliance teams for data pipeline integration.
- Translate business requirements into clear product specifications and actionable data models.
- 2. Data Insight & Reporting
- Develop and manage dashboards that track performance, utilization, and compliance metrics.
- Ensure data reliability, timeliness, and accuracy across internal and partner systems.
- Identify key insights and communicate findings effectively to business stakeholders and management.
- 3. AI & Automation (as a plus)
- Explore opportunities to apply AI/ML for reporting automation, predictive analytics, and trend summarization.
- Collaborate with data scientists or AI engineers (if available) to experiment with insight enhancement models.
- Stay updated on AI technologies relevant to analytics and dashboard intelligence.
- 4. Stakeholder Collaboration
- Work closely with internal and business teams to align data insights with strategic goals.
- Drive continuous improvement of reporting efficiency and user experience in dashboards.
Skills and Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field.
- Min. 4 years experience as a Product Manager, Data Product Owner, or Analytics PM.
- Strong analytical skills with proficiency in data visualization tools (Power BI, Tableau, Looker, etc.).
- Knowledge of data structure, ETL concepts, and data governance.
- Excellent communication, presentation, and stakeholder management skills.
Preferred (Strong Plus)
- Familiarity with AI concepts such as data-driven automation, LLMs, or machine learning models.
- Experience in automated dashboarding, NLP-based reporting, or predictive data analysis.
- Exposure to government compliance systems (TKDN, PDPA, or similar).
- Fluent in English for coordination and reporting.