- Interpret market data trends and patterns to enhance our product’s data accuracy, retrieval speed, and reliability for end users.- Create detailed reports and dashboards to communicate insights effectively to cross-functional teams

Actively pursuing the CFA designation

• Analyzed e-commerce sales data for haircare products, uncovering trends that led to an improvement in brand positioning.• Developed interactive reports and dashboards to effectively track key performance indicators (KPIs) like net margin value (NMV) and units sold.• Collaborated with cross-functional teams to optimize data collection and analysis processes, leveraging in-house data.

• Supported in developing a data-driven curriculum for MBA students, focusing on applying data analysis techniques to real-world business problems (Exploratory Data Analysis, Customer Segmentation).• Delivered training sessions on data exploration and visualization with Excel and Tableau to 60 students across 3 courses, utilizing real-life finance databases.• Collaborated with head lecturer in supervising student tools proficiency through group projects.

• Developed an audio augmentation technique using Additive White Gaussian Noise (AWGN) and applied it to speech data to extract features like Mel-Frequency Cepstral Coefficients (MFCCs) for model training.• Using Pytorch to employ a pre-trained image model CNN (for capturing local patterns) and a Transformer Encoder architecture (for modeling long-range dependencies) to achieve state-of-the-art performance.• Investigated the impact of different hyperparameter settings (e.g., learning rate, batch size, dropout rate) on model performance to optimize the training process and achieve the best possible results