Description: * Completed higher education. * Solid experience in clinical data analysis and modeling, including a deep understanding of health indicators and healthcare metrics (preferably in the context of nephrology, dialysis, or specialized care). * Advanced knowledge of R, Python, SQL, and Power BI, with the ability to handle large datasets and develop high-impact interactive visualizations. * Proficiency in descriptive and inferential statistics, with the ability to build and implement predictive models (e.g., regression, decision trees, random forests, etc.) applied to real-world health problems. * Practical experience with interactive dashboards and automation of analytical processes by developing solutions in R Shiny, Power BI (Power Query, DAX), or other tools that enable faster delivery of insights. * Prior work in healthcare environments (health insurers, hospitals, clinics, or digital health companies), with familiarity in clinical data flows; experience in nephrology or renal care will be a significant advantage. * Advanced English skills, especially for reading technical/scientific articles and preparing reports or presentations for international teams (this professional is expected to interact with materials and stakeholders in English). Additional differentials will include: * Additional academic qualifications: Master's degree or postgraduate studies in Epidemiology, Biostatistics, Public Health, or related fields, demonstrating theoretical depth in health research methods. * Experience in digital transformation in healthcare: Participation in digital transformation or innovation projects in healthcare (e.g., implementation of electronic health records, artificial intelligence in healthcare, telemedicine), demonstrating the ability to navigate technological change initiatives. * Scientific output: Track record of participation in scientific publications, clinical studies, or data-driven research projects, indicating the ability to generate new knowledge and adhere to best practices in data science (documentation, reproducibility, etc.). Responsibilities * Consolidate and validate clinical and operational data from dialysis units, ensuring data integrity, reliability, and comparability of performance indicators across clinics. * Develop interactive dashboards and executive reports to monitor clinical and medical performance indicators, providing clear visibility for the CMO and meeting international reporting requirements. * Create and maintain efficient and auditable ETL (extraction, transformation, loading) processes, ensuring data flows are robust and standardized. * Develop machine learning models and advanced statistical analyses to predict clinical risks, such as probabilities of mortality, hospitalization, treatment non-compliance, or other relevant complications. * Work with large volumes of structured and unstructured data, including clinical records, laboratory results, and operational information, always focusing on generating actionable insights to support medical decisions. * Collaborate with multidisciplinary teams from the Medical Directorate (quality, nursing, medical education, etc.) and international teams, aligning needs and sharing best practices in healthcare data analysis. * Conduct research and exploration of relevant scientific literature (papers, guidelines, clinical studies) to support analyses and substantiate recommendations with up-to-date evidence from nephrology and population health. * Ensure data governance and compliance, adhering to privacy policies (LGPD), information security standards, and the company’s global standards for handling and reporting clinical data. 2511230202461884583