1. Actively clean, process, and validate Data streams for ML model consumption. Contribute to the implementation of MLOps best practices (CI/CD) and risk mitigation strategies as guided by the engineering team.
2. Actively develop and implement Python scripts and small utilities for model features and basic algorithm testing. Ensure development practices align with model fairness and ethical guidelines.
3. Establish and track technical Key Performance Indicators (KPIs) to measure model effectiveness post-deployment. Document and report potential technical risks identified during implementation.
4. Create and maintain a single source of truth for all active Carrier/vendor technical requirements and specifications. Support the definition of project scope, timelines, and milestones.
5. Act as the central liaison between Engineers, Data Scientists, and Business stakeholders. Translate incoming high-level partner requests into clear, detailed, and actionable engineering specifications and tickets.
6. Provide regular, concise updates for stakeholders on project progress, key metrics, and any blockers.
7. Annual salary: 1000K NTD and above
8. Onsite Google Banqiao Office