Angela Maria Garcia
Development
Risaralda, Colombia
Skills
Python
About
Angela Maria Garcia Bermudez's skills align with Programmers (Information and Communication Technology). Angela also has skills associated with IT R&D Professionals (Information and Communication Technology). Angela Maria Garcia Bermudez has 5 years of work experience.
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Work Experience
Freelance
Self employed
January 2022 - Present
- Freelance (Self employed) FreelanceFreelance (Self employed) Freelance Jan 2022 - Present 2 yrs 6 mosJan 2022 to Present 2 yrs 6 mos Bogotá, Distrito Capital, Colombia Remote Bogotá, Distrito Capital, Colombia Remote Role Overview: As a Data Processing and Machine Learning Engineer, I developed and deployed data-driven solutions using Python, focusing on data processing, analysis, and machine learning. Key Responsibilities: Data Processing: Collected, cleaned, and preprocessed large datasets using Pandas and NumPy. Employed ETL processes to integrate data from various sources into centralized databases. Utilized SQL for efficient data querying and manipulation. Machine Learning Development: Developed and trained machine learning models using Scikit-learn, TensorFlow, and Keras. Implemented algorithms for classification, regression, and clustering. Tuned hyperparameters and validated models to optimize performance. Data Analysis and Visualization: Conducted exploratory data analysis (EDA) to uncover insights. Visualized data and model results using Matplotlib and Seaborn. Applied statistical analysis to support decision-making processes. Deployment and Monitoring: Deployed machine learning models using Docker and Kubernetes. Monitored model performance and retrained models as needed. Collaborated with DevOps teams for seamless integration and deployment. Collaboration and Agile Practices: Participated in Agile ceremonies, including sprint planning and daily stand-ups. Worked with data engineers, analysts, and product managers to align project goals. Key Achievements: Developed and deployed multiple machine learning models, improving predictive accuracy and efficiency. Enhanced data processing pipelines, reducing processing time by 40%. Delivered actionable insights through data analysis, supporting strategic decisions. Technologies Used: Data Processing: Python, Pandas, NumPy, SQL Machine Learning: Scikit-learn, TensorFlow, Keras Data Visualization: Matplotlib, Seaborn Deployment: Docker, Kubernetes Tools: Jupyter, Git, JIRARole Overview: As a Data Processing and Machine Learning Engineer, I developed and deployed data Driven solutions using Python, focusing on data processing, analysis, and machine learning. Key Responsibilities: Data Processing: Collected, cleaned, and preprocessed large datasets using Pandas and NumPy. Employed ETL processes to integrate data from various sources into centralized databases. Utilized SQL for efficient data querying and manipulation. Machine Learning Development: Developed and trained machine learning models using Scikit Learn, TensorFlow, and Keras. Implemented algorithms for classification, regression, and clustering. Tuned hyperparameters and validated models to optimize performance. Data Analysis and Visualization: Conducted exploratory data analysis (EDA) to uncover insights. Visualized data and model results using Matplotlib and Seaborn. Applied statistical analysis to support decision Making processes. Deployment and Monitoring: Deployed machine learning models using Docker and Kubernetes. Monitored model performance and retrained models as needed. Collaborated with DevOps teams for seamless integration and deployment. Collaboration and Agile Practices: Participated in Agile ceremonies, including sprint planning and daily stand-ups. Worked with data engineers, analysts, and product managers to align project goals. Key Achievements: Developed and deployed multiple machine learning models, improving predictive accuracy and efficiency. Enhanced data processing pipelines, reducing processing time by 40%. - Delivered actionable insights through data analysis, supporting strategic decisions. Technologies Used: Data Processing: Python, Pandas, NumPy, SQL - Machine Learning: Scikit-learn, TensorFlow, Keras Data Visualization: Matplotlib, Seaborn - Deployment: Docker, Kubernetes Tools: Jupyter, Git, JIRA Skills: Python
Backend Java/Javascript Software Developer
Ideas Fractal SAS, Pereira
July 2021 - December 2021
- | Pereira, Risaralda Actively participate in the development of back end (javascript) and debugging of errors present in the infrastructure of the company's website, including support for SQL databases. Perform CRUD operations: Create and edit tables, update records, and delete tables and schemas from databases. Modification and maintenance of legacy source code. Support and management of projects with the supervision of the systems manager. Second Stage: Developed the Backend using JavaScript and Node.js. Identified and fixed errors in the web infrastructure to improve stability and functionality. Optimize SQL queries and functions to improve application efficiency and accuracy. Handled CRUD operations on databases, including creating, editing and deleting tables. Improved legacy code to meet current requirements. Provide technical support and ensure the implementation of guidelines in projects supervised by the Systems Leader. Data Processing and Machine Learning Engineer FreelancerData Processing and Machine Learning Engineer Freelancer
Freelance SpringBoot Angular Developer/Freelance SpringBoot Angular Developer
Quarter
January 2019 - May 2021
- Freelance (Self employed) - Python Developer FreelanceJan 2019 - May 2021 • 2 yrs 5 mosJan 2019 to May 2021 • 2 yrs 5 mos Bogotá, Distrito Capital, Colombia Remote Bogotá, Distrito Capital, Colombia Remote Role Overview: As a Spring Boot and Angular Developer, I developed and maintained full-stack web applications, focusing on seamless integration and high performance. Key Responsibilities: Back-End Development: Developed RESTful APIs using Spring Boot for efficient data flow and integration. Implemented microservices architecture for modularity and scalability. Used Spring Data JPA for efficient database interactions. Ensured security with Spring Security, managing authentication and authorization. Optimized performance by tuning Spring Boot configurations. Front-End Development: Created dynamic and responsive user interfaces with Angular. Managed state using NgRx for efficient data handling. Used Angular Material for consistent UI components. Integrated Angular apps with RESTful APIs for seamless data exchange. Conducted unit and integration testing with Jasmine and Karma. Collaboration and Agile Practices: Participated in Scrum ceremonies, contributing to effective project management. Collaborated with UI/UX designers, QA engineers, and product managers. Mentored junior developers in Spring Boot and Angular best practices. Continuous Integration and Deployment: Implemented CI/CD pipelines with Jenkins and GitLab CI for automated build, test, and deployment. Managed version control with Git for efficient collaboration. Key Achievements: Delivered multiple full-stack web applications, meeting deadlines and exceeding client expectations. Improved application performance and user experience, increasing user satisfaction by 30%. Reduced bugs and issues by 25% through rigorous testing and code reviews. Technologies Used: Back-End: Spring Boot, Spring Data JPA, Spring Security, Hibernate Front-End: Angular, NgRx, Angular Material, TypeScript Tools: Jenkins, GitLab CI, Git, JIRA, Docker
Education
Centro de Diseño e Innovación Tecnológica Industrial
Fundación Universitaria del Área Andina
March 2022 - June 2024
CISCO NETWORKING ACADEMY
ACADEMY ANI DATA SCIENCE
