Principal Decision Scientist - Marketing

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? 8+ years of experience in a similar role Deep expertise across Acquisition (Paid Search, Paid Social, SEO) and Retention (CRM, Lifecycle, Churn), with the ability to connect channel-level performance to business-wide outcomes Proven, hands-on experience building and deploying Marketing Mix Models (MMM) and incrementality testing frameworks (geo-based, holdout, synthetic control) in a real business context Proficiency in applied statistical modelling, such as LTV modeling, predictive scoring and causal inference techniques Advanced Python or R for statistical analysis, modelling, and automation, with production-quality code standards Practical experience applying AI tools to accelerate, enhance and automate analytical workflows Demonstrated experience architecting scalable data models using SQL and dbt within a modern data stack, including setting standards and reviewing others' work Exceptional ability to distil complex technical findings into clear strategic narratives for non-technical stakeholders and senior leadership Experience working within a high-growth SaaS or digital business with an understanding of unit economics (CAC, LTV, Payback) Demonstrated experience mentoring and developing analysts including coaching on technical skills, analytical thinking and stakeholder engagement Exposure to product analytics or growth functions, with an ability to connect marketing and product data across the funnel Prior experience influencing tooling, vendor or data infrastructure decisions at an organisational level Why Pipedrive?

People-first culture - Be part of a team that values authenticity, champions collaboration, and supports each other—no egos, just teamwork. Work alongside top talent from around the world in an inclusive space where different perspectives fuel our best ideas. Everyone is welcome Unlock potential – Push boundaries, take ownership, and experiment with the latest technologies as we enhance our AI First Vision.

We empower bold ideas that drive real change We’ve got you – Your well-being matters. Enjoy flexible hours, wellness perks and SWAG. Think performance-based bonuses, 28 paid leave days, well-being days, compassionate leave, and even paternal leave—because we take care of ourselves and our people Grow with us – Whether through mentorship, coaching, or internal mobility, we invest in helping you unlock your potential.

Open, honest feedback and clear communication are at our core. We grow together through trust and accountability Packed with purpose – Help 100,000+ small and medium-sized businesses grow and succeed while doing meaningful, customer-driven work Diversity & Inclusion: Pipedrive is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees.

We welcome applications regardless of race, color, religion, age, gender, sexual orientation, gender identity or expression, national origin, disability, veteran status, marital or family status, or any other characteristic protected by applicable law. Eligibility: Please note that for this position, we are only able to consider candidates who already possess the legal right to work in Germany without the need for visa sponsorship or relocation assistance. Background Checks: Where permitted by local law and necessitated by the scope of the role (e.g., access to sensitive data), Pipedrive may conduct a pre-employment background check.

This will be handled in strict accordance with our Candidates Privacy Notice . #LI-Hybrid #LI-VMUC We’re on the lookout for a strategic, hands-on Principal Decision Scientist - Marketing with deep expertise in marketing analytics, experimentation, and statistical modelling, and a strong ability to turn complex data into clear business recommendations that drive measurable commercial impact. If this is something for you, send us your resume (in English) or a link to your LinkedIn profile and please add why we should pay extra attention to your application. Find more English Speaking Jobs in Germany on Arbeitnow

Mostramos trecho e link por vaga, e o texto integral quando a fonte permite. Marcas e logotipos citados pertencem aos seus titulares.

Fonte: Statistisches Bundesamt (Destatis), tabela; dl-de/by-2-0; cálculo da StarIn

Publicada em 31 de out. de 2026

Publicada em 30 de out. de 2026

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