Если вы раньше входили через Google, сбросьте пароль для своей Gmail-почты через кнопку «Забыли пароль?» на экране входа. Затем войдите по email и новому паролю.
Если аккаунта ещё нет, зарегистрируйтесь с Gmail-почтой, после подтверждения почты мы предложим задать пароль.
Что нового
Загружаю обновления...
Что нового
Загружаю обновления...
Работа найдется быстрее с подпискойКандидат найдётся быстрее с подпиской
Чтобы адаптировать резюме под вакансию или составить сопроводительное письмо, загрузите резюме
описание
Acast builds a podcast marketplace that connects podcast creators, advertisers, and listeners. Its marketplace spans more than 140,000 podcasts, 3,300 advertisers, and one billion quarterly listens, monetized across podcast apps and listening platforms.
задачи
Act as the first point of contact for Finance, Product, Sales, and Content Managers with data questions, helping clarify what they need
Own and evolve core reporting infrastructure and data models in dbt and Omni across podcast consumption, listens, views, revenue, payout, and product analytics metrics, structuring business logic so AI agents in Omni can answer stakeholder questions reliably in real time
Build and maintain clear, useful dashboards
Identify patterns and risks in payout, platform, and podcast consumption metrics, and flag them early
Support Content Managers and Product teams with podcast consumption analysis, including listens and views metrics, performance trends, and payout questions
Help Sales understand what the numbers mean for conversations with advertisers
Explain analytical thinking, document decisions, and help teammates continue the work
Collaborate with Analytics Engineers, Data Engineers, developers, and Product Managers to ensure consistency across data models, metrics, and definitions
требования
Listen well and ask follow-up questions before proposing solutions
Have strong SQL and dbt skills and proficiency in BI tools such as Omni
Have experience accelerating analytics development using AI tools such as Cursor or Claude
Take a careful, reliable approach to data, especially finance and payouts
Manage relationships with Finance, Product, Sales, and Content while maintaining clarity under pressure
Work collaboratively, share context, and mentor others where helpful
Translate complex business logic into robust, maintainable data models and clear metric definitions