GoodHabitz

• Design and run the system that connects OKRs to execution across all product teams. • Build the layer that turns signals into action. • Define how teams consume product analytics, customer research, support data, and CS feedback. • Build a reliable operational system around defined KPIs. • Identify where work slows down and fix it. • Improve planning reliability, reduce cycle time from idea to shipped outcome. • Improve how we work with Engineering, Design, Revenue, and Customer Success. • Drive the adoption of high-leverage AI workflows and automate operational work.

GoodHabitz helps organisations build learning habits at scale. We're a B2B SaaS platform operating in the human skills development space — and we're mid-transformation, moving from a sales-led model to one where the product itself drives activation, engagement, and renewal. That transformation is only real if strategy actually becomes execution. Right now, it doesn't always. That's why this role exists. As our first Product Operations Lead, you will build the operating system that connects strategy to outcomes across a growing, multi-team product organisation. You'll own how the product org plans, decides, measures, and ships — not as a process enforcer, but as a system designer who makes the whole machine run faster and more deliberately. **What you'll own ** **Product Operating System ** Design and run the system that connects OKRs to execution across all product teams. This means planning cadences, prioritisation frameworks, documentation standards, and product rituals — built to eliminate ambiguity and reduce coordination overhead, not to add it. **Insights and decision infrastructure ** Build the layer that turns signals into action. You'll define how teams consume product analytics, customer research, support data, and CS feedback — and how that input flows into concrete decisions. The goal is higher signal quality and faster decision velocity. **Metrics operationalisation ** We have defined KPIs. We don't yet have a reliable operational system around them. You'll build it — consistent metric definitions, team-facing dashboards (in partnership with our Product Data Lead), and the review rhythms that make performance visible and trusted. **Execution quality ** Identify where work slows down and fix it. Improve planning reliability, reduce cycle time from idea to shipped outcome, and surface cross-team dependencies before they become blockers. **Cross-functional alignment ** Product doesn't work in isolation. You'll improve how we work with Engineering, Design, Revenue, and Customer Success — aligning on outcomes, improving handoffs, and making sure the right people have the right context at the right time. **AI and tooling enablement ** We are actively building an AI agent layer across the product org. You'll help drive the adoption of high-leverage AI workflows, improve how we use Jira, Slack, and analytics tooling, and automate the operational work that shouldn't require human judgment. **What you won't own ** This role has a clear boundary. The Product Data Lead owns data infrastructure, pipelines, and analytics truth. PMs own product decisions and outcome spaces. You own how the system works — how data is used, how decisions are made, and how execution stays aligned. Product Ops does not own "truth". It ensures truth is used effectively. **What good looks like in 6 months ** - The product operating system is clearly defined, actively used, and trusted by teams - Data flows reliably and teams reference insights in their decisions — not just in retrospectives - Metric ownership is unambiguous, definitions are consistent, and performance is reviewed regularly - Cross-team dependencies are visible and managed before they become fires - Cycle time from idea to shipped outcome is measurably shorter - The AI agent layer has grown, and tangible productivity improvements are visible

GoodHabitz helps organisations build learning habits at scale. We're a B2B SaaS platform operating in the human skills development space — and we're mid-transformation, moving from a sales-led model to one where the product itself drives activation, engagement, and renewal.  That transformation is only real if strategy actually becomes execution. Right now, it doesn't always. That's why this role exists.  As our first Product Operations Lead, you will build the operating system that connects strategy to outcomes across a growing, multi-team product organisation. You'll own how the product org plans, decides, measures, and ships — not as a process enforcer, but as a system designer who makes the whole machine run faster and more deliberately.  What you'll own  Product Operating System  Design and run the system that connects OKRs to execution across all product teams. This means planning cadences, prioritisation frameworks, documentation standards, and product rituals — built to eliminate ambiguity and reduce coordination overhead, not to add it.  Insights and decision infrastructure  Build the layer that turns signals into action. You'll define how teams consume product analytics, customer research, support data, and CS feedback — and how that input flows into concrete decisions. The goal is higher signal quality and faster decision velocity.  Metrics operationalisation  We have defined KPIs. We don't yet have a reliable operational system around them. You'll build it — consistent metric definitions, team-facing dashboards (in partnership with our Product Data Lead), and the review rhythms that make performance visible and trusted.  Execution quality  Identify where work slows down and fix it. Improve planning reliability, reduce cycle time from idea to shipped outcome, and surface cross-team dependencies before they become blockers.  Cross-functional alignment  Product doesn't work in isolation. You'll improve how we work with Engineering, Design, Revenue, and Customer Success — aligning on outcomes, improving handoffs, and making sure the right people have the right context at the right time.  AI and tooling enablement  We are actively building an AI agent layer across the product org. You'll help drive the adoption of high-leverage AI workflows, improve how we use Jira, Slack, and analytics tooling, and automate the operational work that shouldn't require human judgment.  What you won't own  This role has a clear boundary. The Product Data Lead owns data infrastructure, pipelines, and analytics truth. PMs own product decisions and outcome spaces. You own how the system works — how data is used, how decisions are made, and how execution stays aligned.  Product Ops does not own "truth". It ensures truth is used effectively.  What good looks like in 6 months  - The product operating system is clearly defined, actively used, and trusted by teams  - Data flows reliably and teams reference insights in their decisions — not just in retrospectives  - Metric ownership is unambiguous, definitions are consistent, and performance is reviewed regularly  - Cross-team dependencies are visible and managed before they become fires  - Cycle time from idea to shipped outcome is measurably shorter  - The AI agent layer has grown, and tangible productivity improvements are visible

GoodHabitz helps organisations build learning habits at scale. We're a B2B SaaS platform operating in the human skills development space — and we're mid-transformation, moving from a sales-led model to one where the product itself drives activation, engagement, and renewal.  That transformation is only real if strategy actually becomes execution. Right now, it doesn't always. That's why this role exists.  As our first Product Operations Lead, you will build the operating system that connects strategy to outcomes across a growing, multi-team product organisation. You'll own how the product org plans, decides, measures, and ships — not as a process enforcer, but as a system designer who makes the whole machine run faster and more deliberately.  What you'll own  Product Operating System  Design and run the system that connects OKRs to execution across all product teams. This means planning cadences, prioritisation frameworks, documentation standards, and product rituals — built to eliminate ambiguity and reduce coordination overhead, not to add it.  Insights and decision infrastructure  Build the layer that turns signals into action. You'll define how teams consume product analytics, customer research, support data, and CS feedback — and how that input flows into concrete decisions. The goal is higher signal quality and faster decision velocity.  Metrics operationalisation  We have defined KPIs. We don't yet have a reliable operational system around them. You'll build it — consistent metric definitions, team-facing dashboards (in partnership with our Product Data Lead), and the review rhythms that make performance visible and trusted.  Execution quality  Identify where work slows down and fix it. Improve planning reliability, reduce cycle time from idea to shipped outcome, and surface cross-team dependencies before they become blockers.  Cross-functional alignment  Product doesn't work in isolation. You'll improve how we work with Engineering, Design, Revenue, and Customer Success — aligning on outcomes, improving handoffs, and making sure the right people have the right context at the right time.  AI and tooling enablement  We are actively building an AI agent layer across the product org. You'll help drive the adoption of high-leverage AI workflows, improve how we use Jira, Slack, and analytics tooling, and automate the operational work that shouldn't require human judgment.  What you won't own  This role has a clear boundary. The Product Data Lead owns data infrastructure, pipelines, and analytics truth. PMs own product decisions and outcome spaces. You own how the system works — how data is used, how decisions are made, and how execution stays aligned.  Product Ops does not own "truth". It ensures truth is used effectively.  What good looks like in 6 months  - The product operating system is clearly defined, actively used, and trusted by teams  - Data flows reliably and teams reference insights in their decisions — not just in retrospectives  - Metric ownership is unambiguous, definitions are consistent, and performance is reviewed regularly  - Cross-team dependencies are visible and managed before they become fires  - Cycle time from idea to shipped outcome is measurably shorter  - The AI agent layer has grown, and tangible productivity improvements are visible

Note: This role is primarily remote, with the expectation to visit our Eindhoven office around 1–2 times per month for in-person collaboration. At GoodHabitz, we are building an activation-first product strategy that helps learners start, stick, and get value fast — across both LMS-integrated and native platform experiences. We are hiring a Product Data Lead to found and shape the product data discipline from the ground up. This role goes beyond analysis: you will design the event taxonomy, instrumentation standards, and modeled analytics foundations that make product decisions measurably defensible. You will partner closely with Product and Engineering to turn messy, fragmented data into a trusted system (funnels, cohorts, retention), and install a repeatable metrics ritual that enables leadership to steer activation → engagement → retention → GRR with clarity. As the discipline matures, you will help define how product data scales — through systems, processes, and potentially team expansion — based on demonstrated impact rather than pre-set headcount.  This role reports to the Director of Product and will have high visibility across product and executive leadership.  Key Responsibilities Product Data Foundations (Taxonomy + Instrumentation)  - Define and drive adoption of a product event taxonomy and naming conventions for the highest-leverage activation surfaces.  - Partner with engineering to implement and maintain a tracking plan, including clear ownership and change management.  - Establish instrumentation quality monitoring so broken or missing events are detected early.  - Create clear documentation so teams can use events consistently across products and regions.  Activation & Retention Measurement (Funnels + Cohorts)  - Build a working activation funnel that supports segmentation (LMS vs Platform, coach vs no coach, key cohorts), and is used in product reviews.  - Create D0/D7/D14 (and beyond) retention tracking for key cohorts with explicit cohort definitions and repeatable models.  - Translate product questions into robust analysis patterns, and teach teams how to self-serve.  Executive Narrative & Metrics Ritual  - Install a monthly or bi-weekly product metrics ritual with a small set of agreed metrics, definitions, and owners.  - Produce a clear “Activation → Engagement → Retention → GRR” measurement narrative that leadership can rely on.  - Surface risks and data integrity gaps early, and propose sequencing to resolve them.  Cross-Functional Partnership & Structural Enablement  - Clarify the working model between product data, analytics engineering, and domain teams (who builds what, and what gets prioritized).  - Define requirements for critical identifiers and align stakeholders on scope and sequencing.  - Lead the design and sequencing of critical identity plumbing (e.g., account-level joins across product and revenue systems) to enable reliable product → retention analysis.  - Balance speed with rigor: ship practical v1 models and dashboards, then iterate as the system matures.

Note: This role is primarily remote, with the expectation to visit our Eindhoven office around 1–2 times per month for in-person collaboration. At GoodHabitz, we are building an activation-first product strategy that helps learners start, stick, and get value fast — across both LMS-integrated and native platform experiences. We are hiring a Product Data Lead to found and shape the product data discipline from the ground up. This role goes beyond analysis: you will design the event taxonomy, instrumentation standards, and modeled analytics foundations that make product decisions measurably defensible. You will partner closely with Product and Engineering to turn messy, fragmented data into a trusted system (funnels, cohorts, retention), and install a repeatable metrics ritual that enables leadership to steer activation → engagement → retention → GRR with clarity. As the discipline matures, you will help define how product data scales — through systems, processes, and potentially team expansion — based on demonstrated impact rather than pre-set headcount.  This role reports to the Director of Product and will have high visibility across product and executive leadership.  Key Responsibilities Product Data Foundations (Taxonomy + Instrumentation)  - Define and drive adoption of a product event taxonomy and naming conventions for the highest-leverage activation surfaces.  - Partner with engineering to implement and maintain a tracking plan, including clear ownership and change management.  - Establish instrumentation quality monitoring so broken or missing events are detected early.  - Create clear documentation so teams can use events consistently across products and regions.  Activation & Retention Measurement (Funnels + Cohorts)  - Build a working activation funnel that supports segmentation (LMS vs Platform, coach vs no coach, key cohorts), and is used in product reviews.  - Create D0/D7/D14 (and beyond) retention tracking for key cohorts with explicit cohort definitions and repeatable models.  - Translate product questions into robust analysis patterns, and teach teams how to self-serve.  Executive Narrative & Metrics Ritual  - Install a monthly or bi-weekly product metrics ritual with a small set of agreed metrics, definitions, and owners.  - Produce a clear “Activation → Engagement → Retention → GRR” measurement narrative that leadership can rely on.  - Surface risks and data integrity gaps early, and propose sequencing to resolve them.  Cross-Functional Partnership & Structural Enablement  - Clarify the working model between product data, analytics engineering, and domain teams (who builds what, and what gets prioritized).  - Define requirements for critical identifiers and align stakeholders on scope and sequencing.  - Lead the design and sequencing of critical identity plumbing (e.g., account-level joins across product and revenue systems) to enable reliable product → retention analysis.  - Balance speed with rigor: ship practical v1 models and dashboards, then iterate as the system matures.

• Develop and implement a regional marketing strategy for the DACH region, leveraging global initiatives and adapting campaigns to local business objectives and target audience needs • Identify and implement the best market entry strategies; own the regional marketing roadmap in collaboration with local management and the central marketing team • Gain a comprehensive understanding of the ideal customers (ICPs), personas, and the customer journey in the region to ensure demand generation strategies meet their requirements • Utilize various marketing channels (content, events, influencer and partner marketing, email, social media, and paid advertising) to increase demand and engagement in the region • Implement targeted nurturing activities to boost conversions and optimize sales process performance • Align all demand generation activities with consistent brand communication to increase brand recognition and further build trust in the region • Monitor and analyze campaign performance in the DACH region using analytics tools; identify improvement opportunities and implement optimizations to enhance results • Work closely with sales and customer success teams to develop initiatives that support the entire customer journey, from acquisition through retention

• Overall account management for the allocated book of distribution partners. • Drive growth from our partner network through consistent and thoughtful partner engagement strategies, Including sales enablement sessions, lunch and learns, co-marketing campaigns, webinars, (with the partner marketing team) etc to deepen partner relationships and drive mutual success. • Manage a pipeline of inbound new partners and ensure their success within the first 90 days and beyond as they become productive revenue-driving partners • Manage internal GoodHabitz stakeholders including the teams in sales, marketing, integrations, customer success and the design studios. • Guide and manage partners through all elements of the enablement process from integration to activation. • Work collaboratively with other partner success managers to drive global success • Meets assigned targets for profitable sales volume and strategic objectives in assigned partner accounts.

At GoodHabitz, we believe learning should be as engaging as it is impactful. That’s why we’re on a mission to transform how organizations develop their people. Our secret? We create bold, engaging learning experiences that people actually want to complete. Everything is produced in-house at our very own GoodHabitz Studios, where creativity meets learning science to deliver content that drives real behavioral change. This is what you’ll be doing - Your unrivalled commercial skills will help you generate leads and turn them into clients. - Your efficient methods will help you to manage consistent sales pipeline. - Speak and meet with potential clients, give stellar and inspiring presentations about our product and our view on online learning and advise clients on the best ways to use GoodHabitz within their organisation. Win over prospects with your enthusiasm and engagement.

• Du sorgst für die strukturierte Nachverfolgung von Leads aus Events und Marketingaktivitäten, nimmst Kontakt mit potenziellen Kund:innen auf und wandelst diese in wertvolle Termine für unser Sales Team um. • Du gehst proaktiv auf Target Accounts zu, erkennst Potenziale und überzeugst mit einer Kombination aus Charme, Struktur und datenbasierter Ansprache. • Du nutzt bewährte Sales-Methoden, um Gespräche strukturiert zu führen und kontinuierlich bessere Ergebnisse zu erzielen. • Du hältst alle Aktivitäten sauber in Salesforce fest und nutzt das System als deine strategische Geheimwaffe. • Du arbeitest Hand in Hand mit unseren Teams, teilst Insights, optimierst Kampagnen und erreichst gemeinsame Ziele.