Product Manager

An established, highly stable software enterprise specializing in cloud-based data platforms and enterprise solutions for the global supply chain, logistics, and international trade sectors.

The company develops a diverse portfolio of SaaS applications that optimize complex operations, shipping data, and compliance workflows for a global client base.

The R&D center is based in the Central / Extended Sharon region, operating under a flexible hybrid work model (including WFH options).

Position Overview

• Senior Product Manager (Data & AI Platforms) owning the lifecycle of cloud-based data products, telemetry architectures, and intelligent workflows.
• Mapping out market demands and translating complex client operations into scalable, data-driven software solutions.
• Authoring detailed Product Requirement Documents (PRDs) for core data services, internal analytics engines, and AI/ML model integrations.
• Partnering closely with data science, engineering, and business teams to evaluate model performance, understand platform limitations, and define clear success metrics.
• Core Domain & Ecosystem- Product Management, SaaS Platforms, Data Products, AI/ML Productization, Data Modeling, Supply Chain / Logistics Telemetry, PRD Authoring, Data-Driven Decision Making.

Requirements-

• Academic Background: B.Sc. in Computer Science, Software Engineering, Data Analytics, or a closely related quantitative field – Mandatory
• 5+ years of robust professional experience as a Product Manager – preferably focusing on SaaS ecosystems, data-centric products, or platform architecture – Mandatory
• Proven background in inbound product management, directly interfacing with international business clients to extract and define complex technical needs – Mandatory
• Solid technical understanding or hands-on exposure to data models, analytics infrastructure, or machine learning concepts – Mandatory
• Extensive experience writing comprehensive PRDs, with a strong advantage for those tailored to data-driven features or predictive models – Mandatory
• Deep analytical mindset with a strong command of how automated models operate, their constraints, and methods to measure system performance – Mandatory
• Highly independent driver with excellent execution skills and a collaborative approach to cross-functional engineering loops – Mandatory