ÂNderson F.
Data Analyst

Skills

Python

Docker Cloud

Github

Airflow

Mongodb

Sql

ÂNderson is available for hire

Meet ÂNderson F.

All Howdy Candidates are vetted for skills and english proficiency.

Bio

A graduate in Computer Engineering from Universidade Federal do Pampa, with a Master's degree in Applied Computing from the same institution, has developed expertise in image processing for person identification employing the OpenCV library and UAV aerial surveying techniques. Advanced studies included research on pasture prediction through pattern recognition, utilizing neural networks, PostgreSQL databases, Python programming, and remote sensing for comprehensive data collection and analysis.

Data Analyst
6/1/2022 - Present

Expertise developed in data analysis and data science, with a strong proficiency in Python for scripting and data manipulation tasks. Demonstrated extensive use of Docker for containerization and efficient deployment of applications. Regular contributions and version control were managed through GitHub, ensuring seamless collaboration and integration with team workflows. Leveraged Elasticsearch for powerful search and analytics engine capabilities, and utilized Kibana for visualizing complex data sets and creating meaningful insights. Skills honed in these areas ensured robust and effective data solutions.
Data Analyst
5/1/2021 - 5/1/2022

Developed expertise in data analysis and dashboard creation utilizing Metabase and Google Data Studio. Built and implemented Machine Learning models for classification and regression to enhance data intelligence. Contributed to data engineering tasks using SQL and NoSQL databases, including the use of Apache Airflow and DataBricks. Engaged in the creation and modification of ETL processes to support data workflows.
Scholarship Holder
3/1/2020 - 3/1/2021

Developed proficiency in machine learning with a focus on Long Short-Term Memory (LSTM) neural networks and Python programming. Achieved significant expertise in predictive analytics, specifically for forecasting pasture growth in southern Brazilian fields. Leveraged advanced ML frameworks and libraries within Python to build and optimize models. Demonstrated strong analytical and problem-solving skills in the context of agricultural data analysis. Gained experience in data preprocessing, model training, and performance evaluation to ensure accurate and reliable predictions. Created visualizations to present model results and insights effectively.