Product Manager

About the role

We are looking for a highly driven and execution-focused Product professional to own and scale the Swag Store experience. This role sits at the intersection of Product Management, Operations, and AI-driven Analytics, where you will play a key role in driving growth, optimizing user journeys, and improving operational efficiency.

Key ResponsibilitiesProduct Management (Execution-Focused)

Partner with the Product Lead to:

Define and prioritise features for Swag Store:

Write clear PRDs and requirements, especially for ops, analytics, and tooling features

Drive data-backed decisions around:

Discovery, checkout, rewards, and wallet flows

Experimentation (cashback %, denominations, merchandising)

Ensure features are launch-ready with proper instrumentation and operational playbook.

Product Operations

Own day-to-day operations of Swag Store: Catalog, pricing, denominations, offers, cashback rules

Campaign setup and monitoring via internal CMS/admin tools

Monitor live product health:

Conversion, GMV, issuance failures, payment issues, reward discrepancies

Act as the primary ops owner for identifying issues and driving resolution

AI-Driven Analytics & Insights:

Own Swag Store dashboards and key metrics (funnels, GMV, AOV, reward cost)

Use AI/LLMs to:

Analyze funnels and performance trends

Generate insight summaries and experiment readouts

Detect anomalies and sudden metric changes

Turn insights into clear actions or experiments, not just reports

AI, LLMs & Automation

Actively use and configure LLMs for: Analytics queries and summaries

Operational checks

Support issue triage and root-cause analysis

Build or manage AI-powered workflows / agents for:

Campaign validation

Offer or cashback misconfiguration detection

Daily or weekly product health summaries

Continuously identify manual workflows and replace them with AI-driven automation

Success Metrics

Improved conversion, GMV, and cashback efficiency

Faster issue detection and resolution

Reduced manual operational effort through automation

Higher experiment velocity and quality of product decisions

Required Experience:

• 2-4+ years in Product Management, Product Ops, Analytics, or Marketplace roles.
• Strong hands-on experience with AI tools and LLMs (prompting, structured outputs, workflows)
• Experience using data to drive product and operations decisions
• Comfortable working with CMS tools, dashboards, and internal panels