Principal Decision Scientist - Marketing

Pipedrive · Germany, Berlinsenior

In short

▸Líder técnico de análisis avanzado para marketing, transformando datos en decisiones estratégicas.
▸Día a día: construir modelos, marcos de prueba, y traducir hallazgos complejos a recomendaciones ejecutivas.
▸Destacado: impulsa el uso de IA en la analítica de marketing con enfoque práctico y sostenible.

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What they ask for

✓8+ años de experiencia en roles similares
✓Experto en adquisición (PPC, redes, SEO) y retención (CRM, churn)
✓Experiencia probada en modelos de mezcla de marketing (MMM) y pruebas de incremento
✓Habilidades sólidas en modelado estadístico aplicado (LTV, churn, segmentación)
✓Capacidad para traducir resultados complejos a narrativas ejecutivas
✓Experiencia colaborando con equipos de finanzas, producto y tecnología

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dbtSQLPythonRGitBI toolsMarketing data stackExperimentation frameworksAI toolsStatistical modelling

Who should you write to at Pipedrive?

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We believe it takes great people to create a great product. That’s why our team lives our company values, and we hire based on them, too. Since 2010, Pipedrive has been on a mission to support sales and marketing teams with easy-to-use, powerful tools that make everyday work faster and easier. Today, our cloud-based software is trusted by over 100,000 companies and used in 179 countries. We have grown from a five-person team to a truly international company of over 850+ people, representing more than 50 nationalities, with ten offices distributed across Europe and the US. In 2020, Pipedrive received a majority investment from Vista Equity Partners, a global investment firm that invests exclusively in enterprise software, data and technology-enabled businesses, making Pipedrive the fifth unicorn from Estonia. As a Principal Decision Scientist - Marketing, you will lead the development of an analytics function that transforms complex, cross-channel data into strategic insights and measurable business impact. You’ll shape the technical direction for advanced analytics initiatives, driving sophisticated modelling, experimentation, and data infrastructure capabilities that support smarter decision-making across the organization. Operating at the intersection of data science, marketing, and business strategy, you will translate large-scale datasets into actionable recommendations that optimize performance, improve customer outcomes, and support commercial growth. Partnering closely with Marketing, Product, Finance, and Data teams, you will establish scalable measurement frameworks, promote analytical best practices, and influence key business decisions. If you enjoy solving complex problems, working across teams, and turning data into practical business outcomes, we’d love to hear from you! Your new adventure: Lead the design and execution of experimentation frameworks, including geo-based and holdout incrementality testing, to rigorously validate marketing investment decisions at scale Evolve the organisation's Marketing Mix Modelling (MMM) capability, including model development, calibration, and translation into actionable budget allocation recommendations for senior leadership Develop sophisticated statistical models such as LTV prediction, churn scoring, and audience segmentation that influence strategic decisions across Marketing, Finance, and Product Architect and govern the marketing data layer, ensuring best practice across dbt modelling, data quality, and documentation Define and lead cross-functional analytics initiatives that span teams and business units, bringing structure and analytical rigour to ambiguous, high-stakes commercial problems Translate highly complex findings into compelling strategic narratives and executive-ready recommendations, enabling data-driven decisions at the leadership level Partner with Finance (FP&A) to ensure marketing efficiency metrics, budget frameworks, and unit economics (CAC, LTV, Payback Period) are consistent with company-wide financial reporting and planning Collaborate with Data Engineering and Marketing Technology to define and shape the long-term marketing data stack roadmap, ensuring tracking integrity, instrumentation standards, and tooling choices reflect best practice Lead the team’s thinking on how AI tools and techniques can augment the analytics workflow, and act as a practical guide for marketing teams on where and how AI can meaningfully improve their ways of working Does this sound like you?

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