aidata sciencemachine learninga b testingdata architecturedata governancepredictive modelingdata strategydata monetizationcustomer data
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Широкий охватПонятные целиИИ в продуктеРуководство командой
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Текст:
Hirify AI/Оригинал
TL;DR
Director of Customer Data & Data Science (AI): Defining customer data strategy, leading data science, and developing AI-powered digital content products with an accent on business performance, data monetization, predictive modelling, and scalable data foundations. Focus on building high-performing multidisciplinary teams, deploying personalization and recommendation capabilities, and establishing reliable experimentation and governance frameworks.
Location: Berlin, Germany; hybrid policy with remote work allowed up to two days per week and four office meet-ups per year.
Company
hirify.global Group is a European digital content platform operating across 15 markets with 2.5 million users and more than 5,200 publications from 1,100 partner publishers.
What you will do
Define and implement the Group's Customer Data strategy, translating executive priorities into measurable business outcomes across B2C, B2B2C, B2B and CDS business models.
Build KPI frameworks, dashboards, performance funnels and predictive capabilities covering acquisition, engagement, conversion, retention and revenue, including churn prevention models.
Define the customer data monetization strategy, developing first-party data, audience activation, segmentation, identity resolution and measurement foundations for advertising and B2B offerings.
Lead Data Science and AI-powered product innovation, including personalized recommendations, automated daily digest, semantic search and future content discovery features.
Own the technical enablement of the Statsig A/B testing framework and establish reliable measurement of AI and product impact.
Partner with Data Engineering on data quality, accessibility, governance, architecture, SLAs, storage and scalable infrastructure while leading and developing Product Data and Data Science teams.
Requirements
Significant experience in Data Analysis, Data Science, Machine Learning or a closely related data leadership role, ideally in a digital, technology, subscription or media environment.
Strong understanding of business performance analytics, customer behaviour, KPI frameworks and translating complex data into actionable recommendations.
Proven experience leading Data Analysis and/or Data Science teams, managing multidisciplinary teams and developing their capabilities.
Strong understanding of machine learning and predictive modelling, including customer segmentation, churn prediction, personalization or recommendation systems.
Demonstrated experience defining and implementing data strategies or data-driven transformation initiatives.
Solid understanding of data architecture, data pipelines, governance and operational requirements for analytics at scale.
Strong business acumen, including identifying commercial opportunities, challenging stakeholders and connecting data initiatives to measurable outcomes.
Excellent communication and stakeholder management skills across executive leadership, technical teams and operational stakeholders.
Hands-on mindset with the ability to challenge technical and analytical decisions, contribute to problem-solving and drive execution.
Nice to have
Experience with experimentation frameworks, A/B testing and quantitative measurement.
AI knowledge and experience implementing AI strategies.
Understanding of first-party data, audience activation and data monetization opportunities.
Culture & Benefits
Hybrid work with remote work available up to two days per week.
Comprehensive health insurance.
€350 gross well-being allowance paid every December.
Access to Teale mental health support and appointments with psychologists.
VIP access to hirify.global content and four office meet-ups per year with international teams.
Hiring process
HR interview with a Talent Acquisition Manager.
Hiring manager interview with the Chief Strategy Officer, followed by a case study.
Peer interview with the team and a final interview.
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