This is a high-impact, highly visible role with direct influence on customer trust, product strategy, and the evolution of our analytics platform.
What youll do
Own a core Analytics domain end-to-end – from discovery and strategy definition to execution, launch, and continuous improvement.
Define and drive the roadmap for dashboards, metrics, and data experiences serving enterprise marketing teams.
Balance stability, scalability, and innovation in a complex, data-intensive environment.
Lead initiatives that modernize and consolidate analytics capabilities across multiple attribution sources.
Shape the integration of AI-powered capabilities into analytics experiences, enhancing how customers interpret performance data.
Work closely with R&D (Backend, Frontend, Data Engineering) to build scalable, high-performance analytics products.
Partner with Sales and Customer Success to understand customer needs, support adoption, and strengthen trust in our measurement solutions.
Engage directly with customers to validate product direction and identify opportunities to improve clarity, usability, and performance insights.
Drive prioritization in a high-demand environment with multiple stakeholders and competing initiatives.
What you have
5+ years of product management experience, ideally in data-heavy B2B SaaS environments.
Proven experience building and scaling analytics, BI, or data-driven products.
Strong analytical mindset with the ability to define KPIs, interpret data, and use data to guide product decisions.
Experience working closely with engineering and data teams on complex, scalable systems.
Ability to operate in ambiguity and structure complex problem spaces.
Strong stakeholder management skills and experience working cross-functionally in large organizations.
Excellent communication skills, with the ability to explain complex analytical concepts clearly to technical and non-technical audiences.
Experience in AdTech, marketing analytics, attribution, or mobile measurement – strong advantage.
Bonus points
Familiarity with attribution models, SKAN, privacy-related measurement challenges.
Experience consolidating legacy systems or leading platform modernization efforts.
Experience integrating AI or automation into analytics workflows.
Technical background in analytics, data science, or engineering.
