Motivated Data Science trainee with a solid foundation in data analysis, AI, and cloud computing.
Motivated Data Science trainee with a solid foundation in data analysis, AI, and cloud computing. Skilled in extracting actionable insights from complex datasets, optimizing business efficiency, and applying problem-solving strategies. Eager to grow expertise in data science, business analytics through continuous learning and impactful projects.
Expertise in extracting actionable insights from complex datasets, data visualization, and applying statistical and machine learning techniques.
Hands-on experience in building, training, and deploying AI/ML models, including NLP, computer vision, and deep learning applications.
Proficient in building scalable, secure, and cost-efficient AI-driven applications on cloud platforms, with a focus on AWS services.
Foundational knowledge in cybersecurity and strong skills in database administration, optimization, and data pipelines.
Analyzed over 500,000 customer transactions monthly using Python and Tableau, applying statistical and ML techniques to detect patterns and trends in customer behavior.
Impact: Increased actionable insight adoption by 20% within business units over a 6-month period.
Built, trained, and deployed machine learning models using AWS cloud-based ML services, specifically Amazon SageMaker. Applied feature engineering and hyperparameter tuning.
Impact: Gained understanding of scalable ML workflows and MLOps practices on AWS.
Gained hands-on experience in building and deploying AI models, including natural language processing and computer vision applications, using Python libraries like TensorFlow, PyTorch, and Scikit-learn.
Impact: Developed understanding of AI ethics, model interpretability, and performance optimization techniques.
Enabled data-driven decision-making by analyzing over 500,000 customer transactions monthly, increasing actionable insight adoption by 20%.
Built, trained, and deployed machine learning models using AWS cloud-based ML services, including Amazon SageMaker.
Completed hands-on training in Artificial Intelligence and Machine Learning using IBM tools, building and evaluating ML models.
Implemented machine learning models for classification and prediction tasks and applied Natural Language Processing (NLP) techniques.
Developed foundational knowledge of Artificial Intelligence and Generative AI concepts within AWS environments.
Built data visualizations and dashboards for stakeholder presentations and gained practical experience in deployment, migration, and automation.