Promote, together with business areas, the use and application of machine learning to solve problems and improve outcomes;
Build machine learning models capable of identifying business opportunities and enhancing the member experience using internal and external data;
Organize and maintain the model development lifecycle: construction, testing, simulations, deployment to production, presentations, measurement of results and refactoring;
Generate insights through analytics studies to improve member relationships and address their needs (member-centric view);
Act as a promoter of data culture within the organization, improving and demonstrating results achieved through the use of Data Science across various fields.

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;
Data technologies: SQL, Hadoop, Spark;
Programming: Python, PySpark, R, SAS, Scikit-Learn, TensorFlow, Java, Jupyter.

Data Assessor – Data Scientist

Key skills