Itaú Unibanco

Machine Learning Engineer

Amazon Web Services (AWS)

- Member of the Machine Learning technical field community, focusing on machine learning/data science/analytics end-to-end implementations and MLOps/DataOps, using AWS services and open-source frameworks;
- Development of technical architectures with AWS customers and partners, understanding their needs, technical maturity and expected business results;
- Managing opportunities at their technical stage, leading meetings on different types of services and engagements (Demos, POCs, Workshops, Immersion Days) for different levels of stakeholders.

Associate Solutions Architect

mai de 2022 - out de 2022 · 6 meses
- Member of Tech U, a residency program for a select group of new AWS employees. The curriculum is designed to help participants develop technical expertise in cloud computing via project-based learning, creative real-world problem solving, and on-the-job training;
- The program had different sprints focused on developing technical expertise in cloud computing in various areas such as Machine Learning, Big Data, Microservices, Web Dev, and DevOps.

Tech U Resident

Amazon

Supporting Operations, Supply Chain and Transportation teams with statistics and data extraction, cleaning, visualization, and analysis techniques.

- Ownership of the internal Redshift DW at AWS, managing accesses and subscriptions, also performing housekeeping periodically, achieving a saving of 30% in computer and storage costs;
- Developed and owned different daily/weekly/monthly metrics that support the day-to-day Supply Chain Operations (+150 users and stakeholders), adjusting according to their needs;
- Develop ETLs to extract data needed for business analysis, using Spark (Python and SQL);
- Design, develop and maintain automated reports and dashboards that track progress towards business plans, using Tableau and Amazon Quicksight.

Data Business Intelligence Engineer Intern

Suzano

- Perform exploratory data analysis (EDA) to identify possible insights regarding the characteristics of the eucalyptus and cellulose, utilizing NumPy, Pandas, Matplotlib and Seaborn;
- Develop predictive models, using mainly scikit-learn;
- Model tracking with MLFlow;
- Develop APIs to serve models with FastAPI;
- Participation in mentoring sessions, where we teach data science to employees from different areas of the company.

Data Science Intern

ESPM Escola Superior de Propaganda e Marketing

In partnership with the Museum of Tomorrow, the research project focuses on the study and development of a recommendation system for its virtual assistant, IRIS+.

- Conducted data analysis about the recommendations of IRIS+ to the museum visitors;
- Conducted a study about the different types of recommendation systems;
- Developed a new version of the museum's recommendation algorithm, increasing the coverage of recommendations made by IRIS+ by 12%.

Under the supervision of Prof. Dr. Fabrício Jailson Barth.

Undergraduate Researcher

Professional experience with Machine Learning, Data Science, Data Engineering and BI projects, mainly in:

- Developing Machine Learning models with Python (scikit-learn, TensorFlow, PyTorch, MXNet);
- Building MLOps pipelines using open-source projects and AWS services;
- Developing ETL pipelines using Spark (SQL and PySpark);
- Querying large databases with SQL;
- Performing statistical analysis and hypothesis testing;
- Creating different Data Visualization products and reports with Tableau and QuickSight.

Certifications:
- AWS Certified Machine Learning - Specialty
- AWS Certified Solutions Architect – Associate
- AWS Certified Developer – Associate
- AWS Certified Cloud Practitioner

Main Skills: Python, SQL, Dimensional & Relational Model, Machine Learning, Git

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