Program Manager, GM, SMB, Noida

Job description

**Experience** 10-12 years **Education** Engineering (IIT / NIT) , MBA (IIM / equivalent) preferred **Mandate** Own merchant experience & business outcomes for EDC devices, operating at the intersection of Product, Data Science and Operations **Role Overview** The person will sit at the center of Product, Data Science and Operations to define what gets built, why, and how success is measured — converting merchant and market signals into a prioritized roadmap and measurable business outcomes for EDC. **Key Responsibilities** Product Roadmap & Feature Prioritization: Partner with Product to define the EDC roadmap; translate merchant pain points and field feedback into PRDs; prioritize features using impact-effort / RICE-style frameworks; run pilots and track feature adoption post-launch. Data-Driven Decision Making: Partner with Data Science to build activation, usage and retention funnels; run A/B experiments and cohort analysis; build dashboards that turn merchant behavior into a prioritized action list rather than just reporting. Cross-Functional Orchestration: Align Product, Data Science, Operations and Field/Sales teams on a shared roadmap and cadence — weekly reviews, OKR tracking, and escalation of blockers. Business Outcome Ownership: Directly own EDC device activation, usage depth, merchant retention and revenue/take-rate metrics, with accountability comparable to the Soundbox charter. Operations Interlock: Work with Ops on device supply, field deployment and after-sales service quality as inputs to the merchant experience. **Success Metrics (OKR Framework)** Device activation rate and time-to-activation Feature adoption rate against roadmap releases Merchant retention / churn and NPS Revenue / take-rate contribution from EDC merchant base **What We're Looking For** 10-12 years in product, business strategy, or growth roles — fintech, payments, or hardware-led businesses preferred. Engineering degree (IIT or equivalent) plus MBA (IIM or equivalent) preferred. Strong analytical rigor; comfortable working directly with SQL/data tools and Data Science teams, not just consuming their output. Demonstrated ability to lead cross-functionally across Product, Data and Operations without formal authority. Sharp business judgment — able to move from data to a prioritized, defensible roadmap.