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Schedule Interview NowMy journey at Softaims has been defined by curiosity, growth, and collaboration. I’ve always believed that good software is not just built—it’s carefully shaped through understanding, exploration, and iteration. Every project I’ve worked on has taught me something new about how to balance simplicity with depth, and efficiency with creativity. At its core, my work revolves around helping businesses and people achieve more through thoughtful technology. I’ve learned that the most successful projects come from teams that communicate openly and stay adaptable. At Softaims, I’ve had the opportunity to work alongside professionals who challenge assumptions, share knowledge generously, and inspire continuous improvement. I take pride in focusing on the fundamentals—clarity in logic, consistency in design, and empathy in execution. Software is more than a set of features; it’s a reflection of how we think about problems and how we choose to solve them. By maintaining this perspective, I aim to build solutions that are not only effective today but also flexible enough to support the challenges of tomorrow. The culture at Softaims promotes learning as an ongoing process. Every new project feels like a step forward, both personally and professionally. I see each challenge as a chance to refine my skills and contribute to the shared vision of building technology that genuinely improves lives.
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This project aims to develop a comprehensive API for Bitcoin price analysis, providing both historical and real-time data. Built with FastAPI, the API integrates with multiple cryptocurrency exchanges like Coingecko, CoinCap, Binance, and Kraken to deliver accurate and up-to-date pricing information. By focusing on efficiency and scalability, this API serves as a valuable resource for developers, traders, and analysts, facilitating informed decision-making in the volatile cryptocurrency market.
The goal of this project was to predict customer churn for telecommunications companies using machine learning techniques. I implemented Random Forest and XGBoost models to analyse customer data and identify key factors influencing churn. By evaluating model performance with confusion matrices and classification reports, I provided actionable insights to help companies like MTN, Airtel, 9mobile and Outsource Global enhance their customer retention strategies. The project significantly improved decision-making processes, leading to potential revenue growth through reduced churn rates.
The goal of this project was to analyse customer reviews to determine their sentiment positive, negative, or neutral based on the text content of the reviews and associated metadata. Using Natural Language Processing (NLP) techniques, I extracted valuable insights into customer feedback, which helped identify product strengths and weaknesses. The analysis provided actionable insights that enabled the business to improve customer experience and refine product offerings, ultimately driving higher customer satisfaction.
Bachelor of Science (BS) in Statistics
2012-01-01-2016-01-01
Other in Post Graduate Diploma in Management
2020-01-01-2021-01-01