The AI Product Manager Intern will analyze product data, design AI conversation flows, support experimentation, and report findings to stakeholders, focusing on AI-driven product features.
Role Overview
RequirementsRequired Skills
We are looking for an AI Product Manager Intern to support the design, analysis, and optimisation of AI-driven product experiences. You will work on LLM-powered features (e.g., conversational flows, automated follow-ups, internal copilots) and contribute to data-driven product decisions.
This role blends product thinking, analytics, and hands-on work with AI systems.
Key Responsibilities1) Product Analytics & Performance- Analyse product and user data to identify drop-offs, trends, and opportunities
- Define and track key metrics (activation, conversion, retention, task success)
- Build simple dashboards/reports to monitor product performance
- Design conversation flows for AI assistants (e.g., onboarding, support, follow-ups)
- Evaluate conversations using metrics such as response accuracy, resolution rate, and user engagement
- Iterate on flows based on observed user behaviour and edge cases
- Support A/B testing of AI flows, messaging, and product changes
- Document hypotheses, experiment design, and results
- Work with engineers/designers to implement and iterate quickly
- Develop and refine prompts for specific use cases (e.g., sales follow-ups, support responses)
- Implement guardrails (tone, scope control, fallback handling)
- Test prompt variations and document performance differences
- Prepare clear, structured performance reports and presentations for management
- Translate data into actionable product recommendations
- Support weekly reviews and experiment readouts
RequirementsRequired Skills
- AI / Product (Important)
- Basic understanding of LLMs and prompt design
- Familiarity with chatbot / conversational UX principles
- Ability to evaluate AI outputs critically (accuracy, tone, relevance)
- Proficiency in Excel / Google Sheets (pivot tables, basic transformations)
- Data analytics experience with structured and/or unstructured (conversational) data analysis
- Tools: Python, SQL, R, PostHog, GA4, or similar analytics tools
- Exposure to no-code/low-code tools: Zapier, n8n, make.com or similar analytics tools
- Basic familiarity with APIs or data flows
- Ability to create clear PowerPoint/Slides presentations
- Basic UX/UI understanding (user flows, wireframes)
Top Skills
Ga4
Make.Com
N8N
Posthog
Python
R
SQL
Zapier
EPOS Singapore Office
2 Leng Kee Road, Thye Hong Centre, #02-07, Singapore, 159086
Similar Jobs
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
As an Inbound Sales Representative, you'll manage the sales process for SME leads, working closely with Marketing to optimize revenue and ensuring customer needs are met through excellent service and product activation.
Top Skills:
Crm ToolsGoogle SuiteSalesforce
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
The internship focuses on technology development for wet etching and cleaning processes in semiconductor manufacturing, including experimental design, data analysis, and process performance evaluation.
Top Skills:
Data Analysis TechniquesScanning Electron MicroscopyWet CleanWet Etch
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Lead the design and support for gas systems in semiconductor facilities, driving improvements in quality, cost reduction, and sustainability initiatives while mentoring teams and ensuring operational excellence.
Top Skills:
8D Problem SolvingGas SystemsMocPredictive Maintenance ProgramsSemiconductor IndustrySpc
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
