Sales Business Analyst

Docplanner

8d•Remote

About The Position

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 ZnanyLekarz, Doctoralia, MioDottore, DoktorTakvimi, and jameda). Our marketplaces, SaaS and AI tools simplify daily tasks and help doctors, clinics and hospitals work more efficiently, so they can focus on what really matters: caring for for their patients. Your responsibilities will include owning the data structure of the sales organisation in our data warehouse, building the analytical models and automation that enable the team to make faster decisions, and delivering insights under pressure in a fast-moving, flexible environment. This is not a tickets-based role — you will operate with high autonomy, adapting to a changing agenda and proactively surfacing the analyses that matter most for New Business MRR. In this role, you are contributing by… Owning the sales data layer in the data warehouse: Designing, maintaining, and evolving the sales schemas in our data warehouse Ensuring data quality, consistency, and accessibility for the sales organisation Working closely with Data Engineering to align on data models and pipelines Independently leading data analytics and modelling with a focus on New Business MRR: Data queries and solid understanding of data management (SQL, BI tools) Business and financial modelling (forecasting, budget simulations, business analysis) Machine learning application (prediction models, clustering, decision trees, XGBoost) Use of AI tools (ChatGPT, Claude, Copilot or similar) to accelerate analysis and automate repetitive tasks Building internal tools and automations that remove manual effort from the team: Internal tooling development to support sales workflows and reporting Workflow automation using tools like Make, Zapier, Cowork or similar Desirable — proven experience in designing and implementing advanced analytics (data preparation, feature engineering, model validation and productisation) Co-designing, running, and scaling data-driven experiments from one market into global projects

Requirements

3+ years of professional experience
Fluent in English
Ideally a Data Science, Statistics, Math/Physics, Computer Science or quantitatively oriented background
Solid technical expertise — SQL is a must, Python is highly valued
Solid experience designing and querying databases; ideally experience owning or contributing to data warehouse schemas
Knowledge of Tableau / Power BI or other BI tools — ability to edit and create dashboards
Python modelling experience; knowledge of key data science algorithms: clustering, regression, decision trees, XGBoost
Experience with AI tools (ChatGPT, Claude, Copilot or similar) and workflow automation platforms (Make, Zapier, Cowork or similar)
Comfortable working in a fast-paced, flexible environment without a fixed ticket queue — you set your own priorities based on business impact
Ability to work under pressure and deliver rigorous insights to tight deadlines
Proven experience working with multicultural teams and navigating complex organisations
Must already have the legal right to work in your country of residence or the location of the role.

Nice To Haves

Any other language — Spanish, Portuguese, Polish — is a plus
Experience in internal tooling development is a strong plus
Prior experience in SaaS or marketplace business models is a plus
Ability to package insights and communicate with stakeholders, including leading working sessions

Responsibilities

Owning the sales data layer in the data warehouse: Designing, maintaining, and evolving the sales schemas in our data warehouse
Ensuring data quality, consistency, and accessibility for the sales organisation
Working closely with Data Engineering to align on data models and pipelines
Independently leading data analytics and modelling with a focus on New Business MRR
Data queries and solid understanding of data management (SQL, BI tools)
Business and financial modelling (forecasting, budget simulations, business analysis)
Machine learning application (prediction models, clustering, decision trees, XGBoost)
Use of AI tools (ChatGPT, Claude, Copilot or similar) to accelerate analysis and automate repetitive tasks
Building internal tools and automations that remove manual effort from the team
Internal tooling development to support sales workflows and reporting
Workflow automation using tools like Make, Zapier, Cowork or similar
Co-designing, running, and scaling data-driven experiments from one market into global projects