About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people's lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company's products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we're building an AI-native culture. We're not waiting for the future; we're creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what's possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn't been invented yet, you'll fit right in. Senior Product Manager - Retail & Distributor Data Readiness Global | NA + EMEA Initial Scope | Reports to Senior Manager, Enterprise Data Products About the Role We are building a formal Retailer & Distributor Readiness Data Product within Salsify to standardize, govern, and scale how product data flows to retailers and distributors globally. We are hiring a Senior Product Manager - Retail & Distributor Data Readiness to define and own the global data model, standards, and processes required to ensure products are retailer-ready and distributor-ready at launch - without manual rework or downstream surprises. This role will: - Define the Retailer & Distributor Readiness Data Model in Salsify - Align upstream data inputs (Product Development, Brand Marketing) with downstream retailer and distributor needs - Establish global data standards (starting with NA + EMEA) - Transition retailer setup from manual processes to automated channel syndication - Shape how AI can accelerate validation and retailer-specific content creation This is a global, cross-functional role reporting to the Senior Manager of Enterprise Data Products. This role influences broadly across the business but does not directly configure Salsify - execution is delivered in partnership with the Salsify Administrator. Why This Role Exists Today: - Retailer templates exist, but no formalized readiness model - Retailer product setup is largely manual - Salsify's automated channel syndication is underutilized - Upstream and downstream teams experience rework - Required retailer data lacks clarity - Launch timelines are impacted by data gaps We need a dedicated owner of Retailer & Distributor Readiness as a structured, governed data product. What You Will Own 1️⃣ Retailer & Distributor Readiness Data Model - Define the canonical Retailer & Distributor Readiness Data Model in Salsify - Standardize required attributes by retailer and distributor type - Establish global field definitions and naming standards - Define readiness thresholds and completeness criteria - Create global data standards starting with NA + EMEA 2️⃣ Upstream-Downstream Data Alignment - Map retailer requirements to upstream data inputs - Clarify attribute ownership across Product Development and Brand Marketing - Reduce rework between upstream teams and downstream retailer teams - Publish documentation and playbooks for retailer readiness 3️⃣ Retailer Channel Syndication Transformation - Define the roadmap for automated retailer channel syndication - Identify automation candidates across retailers - Define data completeness gates that enable auto-syndication - Partner with Salsify Admin to implement automated feeds - Reduce manual retailer setup processes - Measure automation adoption and manual effort reduction 4️⃣ AI-Driven Enhancements - Define AI use cases for attribute validation and completeness scoring - Shape AI-generated retailer-specific content variants - Establish guardrails for AI-driven data and content workflows - Partner with technical teams to pilot and scale AI capabilities Success Metrics This role is measured by data product outcomes: - % of retailer attributes with defined global ownership - Reduction in retailer-driven rework - Increase in SKUs meeting readiness threshold pre-launch - Increase in automated retailer syndication coverage - Reduction in manual retailer setup hours - Improvement in launch predictability - Adoption of standardized retailer data definitions Required Experience - 5-8+ years in Data Product Management, PIM, Enterprise Data, or similar roles - Experience defining data models for commercial or retail use cases - Experience working with PIM systems (Salsify preferred) - Experience translating business requirements into structured data models - Experience driving cross-functional alignment without direct authority - Strong documentation and stakeholder communication skills Preferred Experience - Experience with GS1 / GDSN - Retail onboarding or digital shelf experience - Experience implementing automated syndication models - Familiarity with AI-enabled content or validation workflows What This Role Is Not - Not a Salsify configuration admin - Not a feed operations specialist - Not an integration engineer - Not a generic data governance analyst This is a Data Product Manager role focused on Retailer & Distributor Readiness as a strategic data product. Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate. The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more. Pay Range $128,200-$165,900 USD Our Culture At SharkNinja, we don't just raise the bar-we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you'll be right at home. What We Offer We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what's possible. When you join, you're not just part of a company-you're part of an outrageously extraordinary community. Together, we won't just launch products-we'll disrupt entire markets. At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja's innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA. Learn more about us: Life At SharkNinja Outrageously Extraordinary SharkNinja Candidate Privacy Notice - For candidates based in all regions, please refer to this Candidate Privacy Notice. - For candidates based in China, please refer to this Candidate Privacy Notice. - For candidates based in Vietnam, please refer to this Candidate Privacy Notice. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, disability, or any other class protected by legislation, and local law. SharkNinja will consider reasonable accommodations consistent with legislation, and local law. If you require a reasonable accommodation to participate in the job application or interview process, please contact SharkNinja People & Culture at accommodations@sharkninja.com

• Lead the ideation and development of innovative features • Own the product roadmap for key platform components like APIs and database integrations • Write compelling epics and user stories • Collaborate closely with developers on design and technical decisions • Bridge product partners and technical teams for seamless communication • Drive Agile processes for successful timely releases

Role Description You'll own the full pricing and monetization domain — from the infrastructure that powers every price we show to the strategy that determines what we charge, how we bundle, and where we expand. This is a transformation role. We're migrating from three disconnected pricing paradigms to a unified dynamic pricing system. The roadmap has 11 priorities, a dedicated engineering team, and no full-time product owner. - What makes this role different: - You own the entire pricing domain: Not a slice of pricing alongside other PM work. Pricing infrastructure, dynamic pricing strategy, new revenue models, service availability — all yours. - Strong data team partnership: A data team owns pricing models and analytics. You define what to optimize. They figure out how. You don't build models — but you speak the language fluently. - Infrastructure-first sequencing: The big pricing gains require a new pricing API and data product first. You need to be the PM who gets energized by building the foundation, not frustrated by it. - What You'll Own: - Dynamic pricing roadmap: Migrate three legacy pricing systems to a unified pricing service. Sequence the 11-priority roadmap, make tradeoff calls, and ship. - Pricing strategy: Define pricing for 24+ services across mowing, non-mowing, and emerging verticals. Balance conversion, margin, and Pro economics. - New revenue models: Unlock bundles, add-ons (e.g., "bag my clippings"), channel discounts, and frequency-based pricing — none of which exist today. - Service availability: Determine where and when we offer services based on supply, demand, and profitability signals. - Experimentation framework: Stand up A/B testing for pricing changes, measuring impact on conversion, margin, and Pro claim rates. - Problems to Solve: - Three pricing systems that can't talk to each other. Architect the migration to a unified system without breaking pricing that 100K+ customers rely on today. - Mowing is 90%+ of revenue and stuck on static pricing. Partner with the data team to build pricing intelligence into mowing without destabilizing the core business. - 24+ services need to migrate, each one different. Define the migration sequence and determine which services get dynamic pricing vs. simplified models. - No bundles or add-ons exist. Design the pricing architecture that makes bundling possible. - What Success Looks Like (Year 1): - Pricing API/service shipped and live — Replaces at least one legacy paradigm with a clear path to consolidating the others. - Mowing on dynamic pricing — Core service running on the new system with measurable margin or conversion impact. - Experimentation framework operational — Team can A/B test pricing changes and measure impact within days, not months. - Bundle/add-on architecture defined — System design complete and engineering building, even if not yet live. Qualifications - AI-native: You use AI daily — scenario modeling, pricing analysis, data exploration, drafting specs. - A systems thinker who architects platforms, not just sets prices. - Data-informed, not data-dependent: You partner with the data team to define what to optimize and interpret results. - Technically fluent: You work directly with engineers on API design and discuss schema tradeoffs. - A patient builder: The pricing gains require infrastructure first — a pricing API, a data product, migration tooling. - Monetization-minded: You see bundles, add-ons, service availability, and frequency pricing as revenue levers. Requirements - This Role Is NOT: - A quick-wins role: Massive technical debt must be addressed before dynamic pricing gains materialize. - A solo act: Every pricing change touches engineering, data, sales, and support. - A data science role: You're not building pricing models. - An optimization-only role: You're building a pricing system from scratch while keeping the current ones running. Compensation & Benefits - Base salary: $140,000 – $175,000 - Equity: Pricing decisions directly impact revenue, margin, and conversion at scale. - Healthcare: Medical, dental, and vision - Fully remote: Pricing work requires deep analysis and focused thinking. - Flexible PTO: We focus on results. Take what you need.

Role Description Teamwork.com is in acceleration mode, with AI at the centre of how we build, run and grow our product. We are embedding AI deeply into the platform, our processes and our team culture - and we are looking for a product leader who has already made that transition, and who thinks and builds differently because of it. As a Senior AI Product Manager, you will own an AI-centric product area used by tens of thousands of teams across the world. You will own not just the backlog, but the problem space and the product strategy — with real autonomy, real accountability and real influence over the direction of products used by millions of people every day. This is a role for someone who has taken AI features and agents from a blank page to something customers rely on, and who can do it again, faster. Qualifications - 5+ years of product management experience in a SaaS or software business, with a clear track record of shipping products that moved meaningful metrics — not just features, but outcomes. - Experience and understanding of lean and agile product development methodologies, and a habit of running product experiments to learn quickly. - Excellent research and analytics skills, including experience undertaking primary customer and user research to inform product strategy. - Exceptional people and communication skills. You are a great collaborator who can rally cross-functional teams and communicate clearly with both technical and non-technical audiences. - The ability to manage multiple priorities and bring clarity, focus and momentum to ambiguous, fast-moving problem spaces. - Experience operating AI in production at scale. You think beyond the prototype — cost modelling at scale, latency budgets, monitoring model behaviour in production, and incident response when something goes wrong. Requirements - You've shipped 0-to-1 AI products and agents. You have a proven track record of taking AI-powered features and agentic workflows from nothing to live, customer-facing products — and you can talk specifically about what you built, the decisions you made, and the impact it had. - You're fluent in evaluation. You have built or operated a golden/eval set, you can measure things like hallucination rate, and you have a view on when to use LLM-as-judge, human raters or structured rubrics — and where each one breaks. You treat evaluation as a core part of the product, not an afterthought. - AI is already how you work. You actively use AI tools in your daily work — for research, synthesis, writing and prototyping. This is not something you are planning to start; it is how you already operate. - You build, not just brief. You have hands-on experience with AI prototyping and development tools (such as Claude, Figma Make, Lovable or similar) and can independently build working proof-of-concepts, going from idea to testable artefact in hours. - You understand how AI systems work. You can hold a substantive conversation about LLMs, agentic workflows, prompt design, RAG and retrieval, orchestration and the trade-offs involved — without needing a translator between you and engineering. - You design for trust and safety. For agentic features you think in terms of scoped permissions, human-in-the-loop confirmation for irreversible actions, spend and rate limits, a clear kill switch, and a defined fallback for the first time the model is confidently wrong in front of a customer. - You partner deeply with applied AI/ML teams. You collaborate day-to-day with ML engineers, applied scientists, researchers and AI designers — assessing feasibility, weighing trade-offs, and turning advanced capabilities into simple, reliable product experiences. Benefits - Competitive salary - Up to 30 days vacation - Pension/Retirement matching - Health plans and wellbeing programs - Give Back program - Educational resources and generous development allowance - Inclusive policies including maternity, paternity and parent leave - Recognition programs - Employee Share Options (ESOP) Company Description Teamwork.com builds an AI-powered platform that helps client-service organisations manage projects, resources, and profitability—helping teams plan, deliver, and improve margins. Our mission is to make teams who deliver client work become efficient, organised, profitable and happy! Our platform has revolutionised how companies keep their client projects on track, their resourcing in check and their profits on point. Combining powerful project management and easily streamlined operations—we’re the only platform built for managing client projects, profitably. Our relentless customer-focus has been rewarded with thousands of amazing customers all across the globe and millions of users who sign in every day. We pride ourselves on creating market leading software, working with outstanding people, and going above and beyond for our customers. Trusted by more than 20,000 teams across 170 countries, Teamwork.com is in acceleration mode as we set our sights to become the undisputed platform for teams who deliver client work.