Senior Data Analyst, Customer Success Ops & AI Insights

Docplanner; Madrid; Hybrid; EUR 65,000 - 90,000; Full time

Benefits offered by this job

Healthcare insurance

Wellness programs

Generous time off

Job summary

Docplanner is seeking a data analytics professional to drive global CS analytics across 13 markets. You will deliver dashboards, data models, and scalable automations while collaborating with BI, Data Platform, and Product Analytics teams.

You will grow analytical modelling capabilities, lead experiments, and translate business needs into impactful analytics with a strong emphasis on AI-first approaches.

Qualifications

• 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 (Amazon Redshift preferred); solid Python for statistical/predictive modelling.
• Working knowledge of statistical modelling (regression, forecasting, A/B testing).
• Hands-on experience with Superset and/or Tableau, dashboards for non-technical audiences.

Responsibilities

• Build and maintain recurring reporting, dashboards (Tableau, Superset), and data models for your business line.
• Develop automations that scale across markets.
• Ensure outputs align with BI dashboard and data standards; escalate gaps when needed.
• Advance analytical modelling (statistics and prediction) over time.
• Build MVPs for new predictive or statistical use cases; hand off to Data Science when validated.
• Contribute to AI-first execution by querying, coding, and analysing faster.

Skills

SQL

Python

Stats modelling

A/B testing

Tableau/Superset

Stakeholder comms

English fluency

Education

Quantitative degree

Tools

Superset

Tableau

Job description

Docplanner is seeking a data analytics professional to drive global CS analytics across 13 markets. You will deliver dashboards, data models, and scalable automations while collaborating with BI, Data Platform, and Product Analytics teams.

You will grow analytical modelling capabilities, lead experiments, and translate business needs into impactful analytics with a strong emphasis on AI-first approaches.