Responsible for intelligence area activities using information production techniques at Unimed. Engaging in risk assessment, decision-making support, and information model development.
Responsibilities
Responsible for intelligence area activities using information production techniques, in compliance with the processes and procedures required by LGPD at Unimed CNU, with the aim of anticipating risk situations and opportunities (financial or otherwise), preventing fraud, and supporting decision-making. Acts as an integrator of information from Unimeds and clients, mapping corporate information of common need, guiding the creation of multidimensional models, working autonomously and serving as a point of reference in the area.
Guide and map risks under supervision, as well as vulnerabilities and deficiencies, monitoring and critically analyzing all processes within the information intelligence area.
Execute procedures and work instructions aimed at optimizing information collection and analysis processes, carrying out and monitoring information search, fusion and dissemination activities.
Conduct data gathering, Big Data activities, OLAP processes, Analytics and produce information to support analysis and decision-making.
Identify predictive information (including regulatory data) required by various departments of the company, including for preventive handling; investigate internal and external incidents, prepare administrative reports and report findings to the Intelligence Coordination and Management.
Identify opportunities and needs for developing new views of historical and predictive information, and define relevant indicators and current information of corporate interest.
Research market information (e.g., ANS) to create and update historical databases, as well as simulate regulatory indicators to positively guide actions.
Monitor and assess whether the information currently published by the information intelligence area presents information security risks.
Requirements
Bachelor's degree in Systems Analysis, Data Processing, Engineering or Business Administration, supplemented by specialization courses or an MBA in related fields.
Proficiency in SQL and Databricks
Knowledge of Python and GitHub
Knowledge of Artificial Intelligence and Machine Learning
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