Promote, together with business areas, the use and application of machine learning to solve problems and improve results;
Build machine learning models capable of identifying business opportunities and improving the member experience using internal and external data;
Organize and maintain the model development lifecycle: development, testing, simulations, deployment to production, presentations, measurement of results, and refactoring;
Generate insights through analytics studies to improve member relationships and meet their needs (member-centered perspective);
Act as a promoter of a data-driven culture within the organization, enhancing and demonstrating results obtained from the use of Data Science across different areas.
Requirements
Education: Engineering, Information Systems, Computer Science, Mathematics, Statistics, Business Administration, or related fields;
Desired skills and knowledge: supervised and unsupervised modeling; Deep Learning; structured and unstructured data;