gantt
    title My Timeline
    dateFormat  YYYY-MM-DD
    section Carreira
    Mestrado em Engenharia Elétrica - Machine Learning  :2020-03-02, 2023-03-02
    TODOS Empreendimentos - Analista de CRM Analytics  :2022-03-28, 2024-04-05
    Bancorbrás - Cientista de Dados Pleno               :2024-04-08,

👨‍🏫 Master of Science in Electrical Engineering from the Federal University of Santa Catarina, specialized in data science and computer vision.

🛠️ Solid experience in Python, implementing machine learning models, and developing Data Science solutions.

📊 Proficient in data modeling using SQL and dbt, ensuring data efficiency and integrity for business areas.

🧑‍💼 Applying data science techniques to solve business challenges related to Customer Relationship Management (CRM).

🏆 Recognized by the ABM (Brazilian Association of Metallurgy, Materials, and Mining) as the best graduate of the Electrical Engineering course in 2019, by Unileste.

📝 🌱 Passionate about continuous learning in the field of Artificial Intelligence. Besides being a private Python and Machine Learning tutor, I share insights about Artificial Intelligence and Data Science on my Instagram profile: Inteligência Programada

• Programming: Python (+4 years), SQL (2 years)
• Machine Learning: Supervised and unsupervised models, Sklearn, TensorFlow, PyTorch, Keras
• Cloud: AWS EC2, AWS Athena, GCP (Vertex AI)
• Data Modeling and Visualization: Power BI, Streamlit, dbt, ETL
• Tools and Platforms: GitHub, AzureDevOps
• Project Management: Agile methodologies (Scrum), Management tools like Monday and Asana

💻 Cientista de Dados Pleno - Bancorbrás (04.2022 - atual)

💻 Analista de CRM Analytics - TODOS Empreendimentos (03.2022 - 04.2024)

🧑‍🎓 Aluno Pesquisador Mestrado - Universidade Federal de Santa Catarina (03.2020 - 03.2023)

1. Churn prediction model: Developed a machine learning model for churn prediction, achieving a 3x higher rate than the company's standard, enabling personalized retention campaigns.
2. Probability model for debt repayment: Calculates the probability of client debt repayment, resulting in +20.5% conversion and +15.3% monthly revenue increase.
3. Default reduction: Estimation of the probability of clients remaining in default, resulting in an average ROI of 190% with reconciliation campaigns.
4. Data Analytics Framework for marketing campaigns: Developed a Python framework and Power BI dashboard for product usage analysis, adhesion history, and marketing campaign tracking.
5. Time to Value (TTV) indicator: Evaluation of the initial value perception of the client using modeling in dbt (AWS Athena) and visualizations in Power BI.
6. Target Audience Segmentation: Precise segmentation of communication channels in marketing campaigns, calculating ROI and LTV projection.

• 📧 Email: [email protected]
• 🔗 LinkedIn: Victor Oliveira
• 📷 Instagram: @inteligencia.programada