- Developing predictive mathematical models (alphas) using advanced machine learning techniques for algorithmic trading.

- Leveraged Python and advanced data science libraries to conduct comprehensive sentiment analysis, revealing key consumer insights and trends from large datasets.- Utilized natural language processing tools and techniques, to interpret customer feedback, crafting data-driven strategic recommendations to enhance brand positioning and development.

- Conducted comprehensive research on startup metrics, industry data, team dynamics, and business models to identify key success factors and product differentiation strategies.- Managed and analyzed data using Open Refine, Excel, and SQL, performing data cleaning, trend analysis, and summary value calculations.- Developed market maps, created data visualizations, and recommended promising startups for further investment evaluation.

- Conducted an extensive literature review and implemented various deep learning models, including VGG16, VGG19, MobileNet, and ResNet, to enhance glitch classification accuracy using the latest LIGO data.-Performed a comprehensive comparative analysis through detailed experimentation and evaluation, incorporating attention modules, label smoothing, and fusion techniques.

- Engineered computer vision solutions utilizing CNN, U-net architecture, and transfer learning methods and Python for effective image segmentation and analysis of astronomical data.