Shannon Simiyu

Trained AI models by evaluating responses across key metrics, including accuracy, informativeness, and correctness.
Provided high-quality code solutions to address instances where models failed to generate accurate outputs.
Delivered prompt feedback to improve model performance and collaborated with team members to resolve project issues effectively.
Labeled and annotated AI datasets, ensuring compliance with project guidelines and maintaining data integrity.
Worked closely with team members to address ambiguities, enhancing project outcomes and upholding the highest standards of data quality.
Collaborated with multiple clients and researchers on successful AI projects, while also applying understanding of SQL and PostgreSQL.

Trained AI models by evaluating responses across key metrics, including accuracy, informativeness, and correctness.
Provided high-quality code solutions to address instances where models failed to generate accurate outputs.
Delivered prompt feedback to improve model performance and collaborated with team members to resolve project issues effectively.
Labeled and annotated AI datasets, ensuring compliance with project guidelines and maintaining data integrity.
Worked closely with team members to address ambiguities, enhancing project outcomes and upholding the highest standards of data quality.
Collaborated with multiple clients and researchers on successful AI projects.

Participated in an intensive 12-month Data Science Bootcamp focusing on data analysis, machine learning, and statistical modeling.
Completed projects, including building data pipelines, conducting exploratory data analysis (EDA), and developing machine learning models for real-world problem-solving.
Gained hands-on experience with tools and technologies such as Python, Pandas, NumPy, SQL, and visualization libraries like Matplotlib and Seaborn.
Demonstrated the ability to translate theoretical knowledge into practical applications by working on end-to-end data science workflows.
Cultivated strong communication, teamwork, and troubleshooting skills through collaborative projects and mentorship sessions.

Participated in an intensive 12-month Data Science Bootcamp focusing on data analysis, machine learning, and statistical modeling.
Completed projects, including building data pipelines and developing machine learning models for real-world problem-solving.
Gained hands-on experience with Python, Pandas, NumPy, SQL, and visualization libraries like Matplotlib and Seaborn.
Worked on end-to-end data science workflows.

Designed and developed custom features for web applications, ensuring user-friendly and efficient functionality.
Built tailored software systems for clients, including school management systems and CRM platforms.
Collaborated with clients to gather requirements, propose solutions, and deliver high-quality software tailored to their needs.
Debugged and optimized existing codebases, ensuring scalability, maintainability, and improved performance.
Integrated third-party APIs and tools to enhance application capabilities and streamline workflows.
Delivered documentation and training materials to assist clients in maintaining and scaling their software solutions.
Managed multiple projects simultaneously, maintaining clear communication and meeting deadlines consistently.
Leveraged data analytics skills to enhance software solutions, working with client datasets to develop features such as reporting dashboards and performance tracking tools.

Designed and developed custom features for web applications.
Built tailored software systems for clients, including school management systems and CRM platforms.
Collaborated with clients to gather requirements and deliver high-quality software.
Debugged and optimized existing codebases.