I am a data professional with 4 years of experience in the technology, acquiring and loyalty sectors of airlines. At the beginning of my career, I participated in the Tech Talent (Trainee) program working in several areas of the data area. I was able to contribute to the development of an AIOps platform, applying Machine Learning to predict hardware problems (capacity), optimizing operations and increasing customer satisfaction.Later, in the acquiring sector, I was responsible for monitoring the performance of card machines, aiming to reduce costs and improve NPS. I created and maintained dashboards with Tableau, developed complex queries in SQL Server and implemented automatic alerts with Python to notify deviations in KPIs, helping stakeholders make accurate decisions. In the HINC platform (NPU), I worked on data integrations in the real estate sector, and explored cloud solutions such as GCP, AWS and Azure using Python for POCs and Java for ETL, in addition to implementing process improvements that increased data quality and accessibility.I currently work as a Data Scientist in the Air Rescue team of Azul's loyalty department, where I create and monitor KPIs and analyze new product opportunities, driving the company's growth. My main tools include SQL Server, Snowflake, Power BI and Python, and I always focus on transforming data into strategic business insights.Main knowledge in: Python, SQL, Power BI, Tableau and Scrum.Fundamental knowledge in: TensorFlow, PyTorch, LLM, AIOps, Grafana, Docker, Apache Airflow, Git, GitLab, BigQuery, Snowflake and Looker.Seeking more knowledge in: AWS, Azure, GCP and Gen AI.