Product Manager, Inventory System

RADAR•San Diego, CA

34d•$100,000 - $200,000

About The Position

As the owner of RADAR’s core product—our real-time, RFID-powered inventory intelligence platform—you’ll lead the evolution of a system trusted to manage billions of dollars in merchandise. Your goal: make RADAR the certified system of record for retailers by delivering near-perfect inventory accuracy (~99%), reducing latency, advancing exit detection, and developing analytics that drive smarter planning and merchandising decisions. You’ll define the API strategy and lead integrations with enterprise systems like Oracle, SAP, and Blue Yonder, ensuring our platform enhances forecasting, allocation, and replenishment processes. You’ll also establish a certification framework to eliminate the need for physical audits, positioning RADAR as the most reliable and intelligent inventory system in retail. Inventory is at the heart of RADAR’s value. Your work will drive the reliability and intelligence that power new pilots, customer expansions, and long-term renewals—ultimately shaping the future of retail operations.

Requirements

You have 6+ years in product management; 2+ years owning enterprise SaaS or mission‑critical systems.
You have proven improvements to reliability, accuracy, or performance metrics.
You have strong technical fluency (APIs, data architecture, algorithm optimization).
You have experience collaborating on ML/AI‑driven products.
You have the ability to communicate technical complexity to executives and customers.

Nice To Haves

You have retail operations expertise: inventory management, merchandising, planning, or supply chain.
You have RFID/IoT product experience in asset tracking, warehouse, or logistics.
You have enterprise retail software background (ERP, WMS, OMS).
You have loss prevention/shrink or audit compliance expertise.
You have forecasting/replenishment/optimization domain knowledge.

Responsibilities

Master platform architecture, accuracy algorithms, and latency constraints.
Assess accuracy, exit detection performance, and technical debt areas.
Meet Customer Success/Ops to capture pain points from key customers.
Review API ecosystem; identify integration gaps and partnership opportunities.
Define a roadmap to achieve ~99% accuracy with clear engineering priorities.
Establish KPIs/dashboards for accuracy, latency, exit detection, reliability.
Collaborate with data science/engineering to optimize algorithms and reduce false positives.
Map certification requirements (audit standards, SOX compliance).
Ship measurable accuracy improvements toward the 99% threshold.
Define a 2026 vision for advanced analytics in planning/merchandising.
Build the business case for expansion beyond apparel (grocery, electronics, pharmacy).
Strengthen partnerships with engineering, data science, and CX leadership.