Вакансии

Location: Vancouver, BC We are looking for a highly skilled and experienced Product Owner - NetSuite to join our dynamic FinTech team. The ideal candidate will have a minimum of 5 years of hands-on experience with NetSuite as an administrator and in implementation roles. This position will be responsible for guiding the direction and management of our NetSuite ERP system in alignment with business requirements and strategy. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you'll achieve : Ensure that the Netsuite remains operational as per defined internal SLAs. Have expert skills in triaging and troubleshooting issues for quick resolution. Collaborate with the Finance Team to identify use cases for Agentic AI Automations to increase productivity. Partner with Internal Audit and Compliance teams on driving SOX compliance, helping with SoD analysis, ITGC, role design and compliance reporting Serve as the primary point of contact for all things related to NetSuite, including feature requests, system configurations, and problem resolution. Collaborate with stakeholders to identify business needs and translate them into technical requirements for system enhancements. Lead NetSuite implementation projects, ensuring on-time delivery and within budget, while meeting the defined objectives and quality standards. Continuously assess and document business processes to identify areas for improvement and implement NetSuite best practices. Coordinate and conduct user training sessions and workshops, including the creation of training materials to ensure staff is knowledgeable and proficient in using the NetSuite system. Develop and maintain detailed project plans and manage resources to ensure successful project execution. Work closely with cross-functional teams, including finance, operations, and Enterprise Technology, to ensure seamless integration with other business systems and processes. Stay informed of new NetSuite features and functionalities, providing recommendations for improvements and enhancements that align with business objectives. About you Minimum of 5 years of hands-on experience with NetSuite as an administrator, including full-cycle implementation experience. Preferably a BS/BA degree in Information Systems or Computer Science or CPA or equivalent practical experience Experience with SuiteScript, SuiteFlow, and SuiteBuilder NetSuite certification(s) such as Administrator, SuiteFoundation, or ERP Consultant Preferred experience with integrating NetSuite with various other SaaS applications like Zuora, Coupa, Anaplan etc. and working knowledge of other surround finance applications like Floqast, Lease Query, Workiva etc. Strong understanding of business processes and accounting principles. Proven project management skills, with the ability to manage multiple priorities and projects simultaneously. Excellent problem-solving and analytical skills, with a strong attention to detail. Exceptional communication and interpersonal skills, with the ability to work effectively with both technical and non-technical stakeholders. Ability to adapt to a fast-paced, evolving environment and quickly grasp new concepts and technologies. Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply. What we’ll offer Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit. For this role, the estimated base salary range is between CAD 136,000–155,000.The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified. In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role. We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role. #LI-Hybrid #LI-SA About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

— будет отвечать за продуктовую стратегию по B2C направлению. — проведёт discovery: интервью, анализ воронок, прототипы.

Задачи: Senior Product Manager в быстрорастущий AI-companion продукт. Требования: - Опыт работы в Product Management не менее 4 лет, преимущественно в B2C. - Навыки в growth и монетизации, включая activation, retention, conversion, LTV. - Опыт работы в продуктовой компании. - Опыт с подписочными продуктами, предпочтительно web2web или web2app. Условия: - Удалённая работа из Польши или Кипра. - Полная занятость.

Задачи: — Запуск и развитие продукта с нуля на рынки США, ЕС и Латинской Америки. Условия: — Работа в PropTech-стартапе, связанная с созданием 3D-моделей, цифровых двойников и интерактивных VR-туров для недвижимости. — Частичная занятость (Part-time). — Удалённый формат работы с возможностью работать из любой точки мира.

Задачи: Управление продуктовыми офисами в крупной розничной сети формата дискаунтера. Требования: — Опыт в продуктовом управлении не менее 3 лет на позициях Senior PM, Lead PM или Head of Product. — Опыт работы в ритейле, логистике, FMCG или e-commerce от 2 лет. — Опыт управления 1–2 продуктовыми командами численностью от 5 до 15 человек. Условия: Работа в офисе в городе Набережные Челны.

Задачи: Ищу Product Manager для работы с мобильными приложениями и рекламной монетизацией. Требования: Грейд Middle или Senior. Условия: Работа удалённая вне РФ, РБ и Украины, в таймзонах Европы и Азии. Долгосрочный контракт B2B, фуллтайм. Компания: заказчик — компания с Кипра, развивающая собственные мобильные приложения с рекламной монетизацией.

Задачи: — Управление продуктом в сфере Health & Fitness. Требования: — Опыт работы на позиции Lead Product Manager. — Будет плюсом опыт работы с подписочной моделью монетизации. Условия: — Работа в молодой команде экспертов. — Удалённый формат работы по всему миру.

Задачи: — запуск продуктов с нуля в области рассрочки и BNPL, а также карты рассрочки. Требования: — опыт работы Product Owner в банке и с кредитными продуктами. — знание финтех-рынка Узбекистана будет преимуществом. Условия: — полный рабочий день. — работа в офисе в Ташкенте. — возможность влиять на продукт и принимать быстрые решения без бюрократии.

Responsibilities: — Build and launch a proprietary Sportsbook platform from scratch. Conditions: — Location: Limassol, Cyprus. — Relocation can be discussed.

Задачи: — Формирование продуктовой стратегии. — Управление командой. — Приоритизация инициатив. — Ответственность за бизнес-результат. Требования: — Опыт управления продуктами и командами обязателен.

Задачи: — Запуск продукта с нуля (0→1) в сфере виртуальных карт на базе международного банка (white-label) для аудитории СНГ-экспатов за границей. — Работа с метриками LTV, CAC, ROI. — Развитие продукта на рынках СНГ и международных. — Привлечение пользователей в сложных финансовых нишах. Требования: — Опыт работы в финтехе, подписочных сервисах или карточных продуктах. — Техническая грамотность. Условия: — Удалённая работа с возможностью работать из любой страны.

Location: (Multiple States), United Kingdom About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Germany About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), France About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Ireland About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Spain About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Portugal About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Netherlands About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement