Company Description At Docplanner Group, we're on a mission to help people live longer, healthier lives. As the world's largest healthcare platform, each month, we connect 24 million patients with 280k doctors across 13 countries (through brands like Znany Lekarz, Doctoralia, Mio Dottore, Doktor Takvimi, and jameda). At scale, yet agile – 3,000+ employees, but still fast, versátil, and hands-on.

Docplanner's Customer Success organisation serves hundreds of thousands of healthcare professionals across 13 markets. Two global business lines sit at the centre of that effort, Individual Doctors and Clinics, each led by a VP who needs sharp, reliable analytics to grow their business and make decisions with confidence. This role sits within Global Customer Success Operations & Analytics, the team that acts as the connective layer between the business and Docplanner's data organisation: BI (dashboard and data standardisation), Data Platform (infrastructure, architecture, DWH), and Product Analytics (product launches and opportunities).

This role is dedicated to one business line, partnering closely with that VP and their leadership team on the deep dives, data models, dashboards, and experiments needed to run and grow the business across our 13 markets. You'll report to the Global CS Ops analytics manager, who sets the team's priorities and supports big projects the team takes on. Within that frame, you own how your own time is spent day to day, prioritizing incoming asks, sequencing your backlog, and deciding what needs your manager's input versus what you can resolve directly with your business and data stakeholders.

Reporting, dashboards & data models Build and maintain the recurring reporting, dashboards (Tableau, superset), and data models your business line runs on Build and maintain automations that scale across markets Keep outputs consistent with BI's dashboard and data standards, escalating gaps rather than working around them Analytical models: statistics & prediction (a growing focus)Today, most of your time goes to reporting and execution. Over the next year, we expect a meaningful shift toward analytical modelling (statistics and prediction)Review, update, and improve the statistical and predictive models your business line already relies on Build MVPs for new predictive or statistical use cases, handing them off to Data Science once validated Bring regression, forecasting, and other statistical techniques into your day-to-day analysis, not just descriptive reporting AI-first execution Work AI-first: use AI to query, code,



and analyse faster and more consistently Use and contribute to the team's shared libraries, reusable code, and architecture (e.g. Git Hub-based repositories)Bridging business and data teams Act as the translation layer between your business line and Docplanner's data organisation: BI, Data Platform, and Product Analytics Bring the right requirements to each team, and flag when scope or timelines don't match business priority Driving analytics for your business line Partner directly with the VP of your assigned business line and their team to understand the business, identify gaps, and surface opportunities Lead deep dives that go beyond describing what happened to explain why, and what do next Propose, run, and analyse experiments (A/B tests and beyond) that inform business decisions Prioritisation & stakeholder alignment Own the day-to-day sequencing of your own workload: triage incoming requests, judge urgency and impact, and decide what to tackle first without waiting to be told Align directly with assigned business and data stakeholders on what matters and when Escalate cross-team or resourcing trade-offs to your manager, who owns prioritisation of the team's big projects Qualifications What will help you thrive?

Degree in a quantitative field (Engineering, Statistics, Mathematics, Physics, or similar)+3-5 years of relevant analytics experience as an individual contributor Very good SQL skills (Big Query preferred); solid Python, especially for statistical and predictive modelling Working knowledge of statistical modelling (regression analysis, forecasting/prediction, A/B testing)Hands-on experience with Looker and/or Tableau, building dashboards for non-technical audiences Skilled at digesting complex data into business language: able to summarise findings and frame them as a clear narrative, not just a report Experience working cross-functionally, partnering with non-technical stakeholders across departments Professional fluency in English (Spanish is a plus)What makes you a strong fit?

Proactive by default: you spot what needs doing and raise the level of execution around you, rather than waiting for instructions Owner with entrepreneurial mindset: own your work, your results, and everything in between Able to prioritise your own workload with sound criteria,



and know when to align with stakeholders versus escalate to your manager Comfortable navigating ambiguity, driven by results Understands the capabilities and limits of AI/LLMs and has experience building things with them (professionally or on your own)Track record of scoping problems, running high-quality quantitative analysis, and developing insights that drive decisions Communicates complex concepts simply and clearly; builds trust across a wide range of stakeholders Extra advantage Experience building or validating statistical/predictive models and handing them off to a Data Science team Experience in tech companies, start-ups, and/or consultancy. Here's what the process usually looks like (though it might vary slightly depending on the role): Intro Chat – A first call with our Talent Partner Ashleigh Hillto explore mutual fit around relevant skills, value alignment, and motivation. Take this chance to ask anything on your mind - it's just as much about making sure we're the right fit for you, too.

Technical

Interview – A short SQL assessment and discussion with our Head of BI. Additional/ Final Interview (Optional) – A final conversation with another senior leader/stakeholder/peer from our Global Team. Why You'll Love It Here Integral Benefits – No matter where you are, you'll have access to: Healthcare insurance – so you can focus on what matters. Time off that counts – whether it's a vacation, your birthday, or just a day to recharge, we believe in balance.

Local

Perks – Depending on your location, you will be entitled to local benefits like meal vouchers, transport allowances, or extended parental leave. You'll find lots of chances to learn, develop, and explore new paths - whether within your team or through cross-functional projects. A Truly Global Team – Work with talented people from all over the world in a diverse and inclusive environment.

Flexibility That

Works for You – Remote work and flexible hours aren't just buzzwords here. Prefer an office setting? At this time, we are not able to sponsor visas for this position. To apply, you must already have the legal right to work in your country of residence or the location of the role.

Keep it simple, keep it lean – smart solutions over complexity. Don't just take our word for it—check out our Glassdoor to hear what our people say!_________________________________________________________________________Madrid Address Barcelona, 08019 Employment Type Full time Location Type Remote Department Docplanner Deadline to Apply October 26, 2026 at 10:00 AM UTC

📌 Senior Data Analyst (Customer Success Operations) (Barcelona)
🏢 Docplanner
📍 Barcelona