Product Manager

ToolsGroup delivers AI-powered supply chain and retail planning solutions that help companies forecast demand, optimize inventory, and improve replenishment decisions. They are seeking a Product Manager to own strategy and product planning for their Retail Inventory solutions, focusing on allocation, replenishment planning, and inventory optimization.

Responsibilities:

• Own Strategy & Product Direction (Outcomes-first)
• Develop and communicate a clear product strategy and roadmap for Retail Inventory (Allocation + Replenishment + network inventory optimization), grounded in customer problems, market dynamics, and ToolsGroup’s product vision
• Define the problems to solve (not just features to ship), align stakeholders on desired outcomes, and ensure delivery focuses on customer value and business impact (adoption, retention, expansion, margin/service improvements)
• Identify and prioritize the highest-value use cases across omnichannel retail (store/DC/e-comm), including exception management, automation, and “what-if” decisioning
• Lead Continuous Discovery with an Empowered Team
• Partner with engineering and design to run ongoing discovery: customer interviews, workflow mapping (“day-in-the-life”), prototype testing, and data/telemetry review
• Ensure solutions are valuable, usable, feasible, and viable—and that teams can iterate quickly based on evidence
• Translate learning into sharp product bets: clear success metrics, hypotheses, rollout plans, and iteration loops
• Translate Strategy into Roadmaps, Requirements & Execution
• Convert strategy into a prioritized roadmap/backlog with crisp problem statements, user outcomes, and acceptance criteria; maintain ongoing alignment with cross-functional stakeholders
• Collaborate with delivery leaders to ensure the team ships increments that deliver measurable outcomes, not just output
• Define packaging/positioning inputs for Retail Inventory capabilities, including how allocation and replenishment capabilities are described and sold, ensuring consistency in how customers understand the value
• Be the Product Expert & Evangelist (Internal + External)
• Act as a subject matter expert for retail inventory planning workflows (allocation, replenishment, inventory balancing) and the data/decision flows behind them
• Support Sales and customer-facing teams (pre-sales, value engineering, implementation, customer success) by translating retailer needs into product direction and enabling successful adoption
• Partner with Product Marketing on messaging, competitive differentiation, and launch readiness

Requirements:

• 3+ years Product Management experience in retail inventory solutions (allocation, replenishment, MEIO, store/DC planning) or adjacent retail solution space (e.g., OMS, fulfillment, merchandising planning, supply planning) OR
• 5+ years' experience as a Retail Planner (e.g., allocation, replenishment, merchandise planning, assortment planning) with strong understanding of retailer pain points, decision processes, and tradeoffs
• Working knowledge of allocation and replenishment planning concepts (service levels, lead times, safety stock, presentation minimums, seasonality, constraints, exceptions, network inventory tradeoffs) and how retailers operationalize these decisions
• Ability to frame problems, prioritize based on evidence, and guide cross-functional teams through ambiguity to deliver outcomes
• Strong written and verbal communication skills; comfortable translating between executive narratives and detailed workflows
• Strong collaboration to align stakeholders without relying on authority, and you build clarity across product, engineering, sales, and customer teams
• Experience supporting enterprise SaaS go-to-market motions: RFPs, solution validation, implementation feedback loops, and enablement
• Experience with (or familiarity with) retail planning vendors and domains such as RELEX / Blue Yonder / o9 (or comparable)
• Understanding of Typical technology ecosystems present in a retailer's enterprise and the data constructs and integration patterns typical
• Exposure to AI/ML-driven forecasting/optimization and how probabilistic approaches improve decisioning under uncertainty