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DocPlanner Group is the world's largest healthcare platform, connecting 24 million patients with 280k doctors across 13 countries. The company operates multiple brands (ZnanyLekarz, Doctoralia, MioDottore, DoktorTakvimi, jameda) and provides marketplaces, SaaS, and AI tools to help healthcare providers work more efficiently.
This Global Strategy Analyst role is central to building the next generation of DocPlanner's Customer Success function. You will combine strategy, analytics, and technical project management to help scale from fragmented local practices into a cohesive, AI-first global operation while respecting local market nuances.
Key responsibilities include:
• Design and build the global Customer Success function across three pillars: customer insights (journey customization, research, experimentation), productivity (product automations, operations optimization), and best practices (cross-market sharing, benchmarking).
• Lead the definition, testing, and rollout of AI-first Customer Success use cases—prioritizing by impact, ensuring practical adoption, and thinking ahead on scalability.
• Independently conduct data analytics and modeling focused on retention and growth, including SQL queries, dashboard creation in Superset/Tableau, machine learning applications (prediction models, clustering, decision trees), and business/financial modeling.
• Support execution of strategic projects across DocPlanner's markets, scaling experiments from one market into global initiatives, liaising with in-market stakeholders, and acting as technical project manager for selected initiatives.
You bring 3–5 years of experience in strategy, operations, analytics, or project management, ideally with a quantitative background (Data Science, Statistics, Math, Physics, CS, Finance). Technical skills include SQL, DBT, Superset/Tableau, and ideally Python for data science modeling. You have proven experience in business analysis, financial modeling, and forecasting. You're comfortable working with multicultural teams, communicating insights to stakeholders, and collaborating across data engineering and product teams. Fluency in English is required; Spanish, Portuguese, or Polish is a plus.
