As an Associate Data & AI Engineer at Capgemini Engineering, I have contributed to a wide range of AI and data science projects, including LLM-based HR chatbots, and Neural Machine Translation (NMT) systems. Contributed in model optimization for deployment on edge devices, implemented large language models (LLM) for Mac, and built pipelines for exploratory data analysis. Additionally, I led a team in deploying real-time object detection systems and contributed to data-driven initiatives for Rogers, enhancing location-based services. My role has involved working with technologies such as Python, PyTorch, TensorFlow, Docker, and AWS, focusing on model optimization, cloud deployment, and scalable AI solutions.

As a Data Science & ML Trainee Engineer at AlmaBetter, I worked on various data science and machine learning projects, including credit card default prediction, sales forecasting, and image classification. I performed data analysis, applied advanced feature engineering, and built machine learning models like Logistic Regression, Random Forest, and ARIMA/SARIMA. I also developed deep learning models using CNN for image classification. My work involved leveraging Python, machine learning libraries, and deep learning frameworks to deliver optimized solutions across multiple domains.

As a Data Analyst, I specialized in managing and organizing customer data, ensuring data quality through cleaning and standardization processes. I created insightful visualizations and interactive dashboards to convey complex information effectively. My work included generating detailed reports and delivering actionable insights to stakeholders. I utilized Python and Excel to support efficient data management and analysis throughout my role.