Product Manager

• Own the vision, priorities, roadmap, and measurable outcomes for your product area, balancing customer value, operational impact, commercial priorities, and technical complexity.
• Lead discovery and prioritisation for complex customer and operational problems, using user research, product and operational data, market insight, and commercial context to determine where the team should focus.
• Experience working closely with engineers and designers throughout discovery, solution design and delivery, without relying on heavy hand-offs or excessive documentation.
• Map and redesign freight and operational processes to identify opportunities for technology, automation, and AI to reduce friction and improve decision-making.
• Define success measures before development begins and use product data, customer feedback, and operational insight to assess whether released solutions are delivering the intended outcome.
• Take responsibility for initiatives beyond launch, ensuring solutions are adopted, create measurable value, and are improved based on evidence.
• Facilitate sessions and communicate effectively to align product, engineering, design, operations, commercial, and leadership teams around priorities and decisions.
• Contribute to the broader product strategy and roadmap that advances our vision of intelligent supply chains.
• Use AI tools as part of your day-to-day product practice to improve the speed and quality of research, analysis, prototyping, communication, and delivery.

• Define and own your domain's quarterly goals and success metrics
• Run structured discovery: customer interviews, behavioral analysis, funnel review, and data exploration
• Write engineering-ready specs — clear, with edge cases covered and no open questions left
• Partner directly with PM Growth on experiment design and high-velocity delivery
• Collaborate with GTM (Sales, CSM, PMM) to resolve enterprise-critical issues and translate client needs into scalable product improvements
• Track product health and understand what's driving changes — with clear attribution and causal reasoning
• Use AI as a default tool across research, analysis, spec writing, and communication

Product Manager – Core Products & Platform

• Hire, coach, and develop Product Managers across multiple product areas.
• Build an autonomous, high-performing team with a strong culture of ownership, accountability, and continuous improvement.
• Translate company strategy into measurable product outcomes.
• Drive prioritization based on business impact and customer value.
• Ensure roadmap investments deliver measurable results.
• Own portfolio planning and roadmap alignment across multiple teams.
• Improve delivery predictability, execution quality, and cross-functional coordination.
• Balance customer value, technical investments, and long-term product sustainability.
• Establish operating mechanisms, planning frameworks, and Product Management best practices that enable organizational scale.
• Continuously improve decision-making, prioritization, and execution quality.
• Raise the hiring bar, develop future Product leaders, and help shape the evolution of the Product organization.
• Foster strong collaboration across Product, Engineering, Design, Analytics, and GTM.
• Apply AI to accelerate research, planning, decision-making, and communication.
• Help the team adopt AI-enabled workflows that improve productivity and execution quality.

Senior Group Product Manager

• Own the full product lifecycle: discovery, prioritisation, specs, delivery, and iteration
• Map current manual operations (partner analytics, escalations, write-offs, refunds, chargebacks) and systematically eliminate them through product solutions
• Build a product that surfaces cost-reduction opportunities automatically — replacing manual reporting cycles with real-time signals
• Design partner-facing flows that resolve issues without human escalation: automated write-off processing, refund/chargeback handling, payout adjustment logic
• Define and instrument the metrics that prove the product is working: cost per partner, manual task volume, resolution time, revshare rate trends
• Work directly with engineering and data teams to ship: write clear specs, unblock development, own the roadmap
• Identify and integrate tooling (CRM automation, reporting pipelines, workflow engines) that reduces manual overhead across the team
• Deliver a long-term initiatives roadmap with clear, measurable financial impact

Cost Optimization Product Manager

• Own the Options product area end-to-end, including discovery, roadmap, prioritization, delivery, and business outcomes. Act as the primary product owner for options trading while contributing to other strategic product initiatives across the platform
• Drive continuous product discovery by working closely with customers, stakeholders, engineering, and design to identify opportunities, validate assumptions, and solve high-impact customer and business problems
• Define and monitor key product metrics across adoption, engagement, retention, trading activity, customer satisfaction, and revenue. Use data, experimentation, and customer insights to drive product decisions and measurable outcomes
• Lead delivery of product initiatives from concept to release, ensuring clear requirements, alignment across teams, and successful execution. Partner closely with engineering to balance customer value, technical excellence, and platform stability
• Contribute to the evolution of product management practices, product operating model, and AI adoption across the organization

Product Owner

• Build and maintain a prioritized Lab portfolio/backlog with clear hypotheses, expected upside, effort, dependencies, and status.
• Define the riskiest assumptions for each bet and design experiments with explicit kill criteria.
• Run fast experiments (spikes, prototypes, wizard-of-oz, pilots) and ship “just enough” product to learn—without overbuilding.
• Partner tightly with engineering and design to deliver pilots and instrument them to capture meaningful signals.
• Synthesize outcomes into crisp decisions: Scale / Iterate / Pivot / Kill—and prevent “zombie projects.”
• Create lightweight decision logs and learning summaries to keep leadership and GTM aligned.
• Identify GTM dependencies early (positioning, enablement, pricing, legal, support, etc.) and coordinate cross-functionally.
• When signal is strong, prepare a clean handoff package (what was validated, evidence, remaining risks, success metrics, recommended scaling plan).

Senior Product Manager, Lab

• Define the Gift Cart strategy and translate it into a roadmap — with clear priorities and reasoning behind every decision.
• Communicate with customers and CSMs regularly, and analyze data together with the analytics team — to find growth opportunities and make informed decisions.
• Write specifications that engineers can build from — with detailed requirements and edge cases covered.
• Take features from idea to launch, working closely with design and engineering at every step.
• Track product health and growth: conversion, average gift size, error rates — and understand what's driving them.
• Prepare CSMs and Sales for every launch so they're always in context ahead of time.
• Keep stakeholders aligned — on priorities, timelines, and changes in plans.

Senior Product Manager, Gift Cart

• Define the vision, strategy, and roadmap for AI/ML product features (JobHunt Engine).
• Take full ownership of the product lifecycle from hypothesis to scaled impact, focusing on business results, not just model performance.
• Translate business problems into ML hypotheses and solutions.
• Work side-by-side with ML engineers and data scientists to define data requirements, evaluation frameworks (evals, RAG, agents), model monitoring, and delivery processes.
• Design and execute rapid, pragmatic validation cycles.
• Formulate clear hypotheses (Problem → Mechanism → Impact → Metric), choose the right validation method (A/B test, shadow model, phased rollout), and make data-driven go/no-go decisions under uncertainty.
• Apply critical thinking to decompose complex, ambiguous problems.
• Collaborate closely with Engineering, Data Science, and business teams. Communicate complex ML concepts clearly and align stakeholders on goals, trade-offs, and progress.

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