Ayobami Adeolu Adeyeye

In this project, I single-handedly designed and implemented a sophisticated model to forecast cryptocurrency prices, leveraging the dual powers of sentiment analysis from Twitter data and the examination of historical cryptocurrency values. By integrating state-of-the-art NLP techniques—specifically BERT for understanding the sentiment of tweets and LSTM for analyzing time-series data—I aimed to uncover the nuanced relationship between public sentiment expressed on social media and its subsequent impact on cryptocurrency market dynamics.

This endeavor required a deep dive into machine learning and data science and an understanding of financial markets and social media analytics. My work demonstrates the potential of combining sentiment analysis with historical data analysis to enhance the accuracy of financial predictions, offering valuable insights for investors and researchers alike.

To address customer churn in the telecom sector, I utilized a dataset with approximately 100,000 records and 100 variables detailing customer attributes and behaviors. The goal was to predict which customers were at risk of churning by analyzing this rich dataset to understand the key factors influencing churn in the telecom industry.

Employing data science techniques and machine learning algorithms, I developed a predictive model capable of identifying potential churners with high accuracy. This model leveraged the intricate relationships between various industry-specific variables to offer insights into customer retention strategies. The application of this model presented a proactive means to reduce churn by enabling targeted interventions for at-risk customers—enhancing customer satisfaction and loyalty.

This endeavor demonstrated my proficiency in handling complex datasets, developing predictive analytics models, and applying data science to solve real-world business challenges—highlighting the potential of analytics in improving business outcomes within the telecom sector.

I crafted a business intelligence report for Sabadex, delving into sales data, customer demographics, marketing efficacy, and overall business operations to derive actionable insights for strategic growth. The analysis revealed key sales trends and product metrics, underscoring the importance of adaptive inventory management and precise marketing efforts. The study of customer demographics highlighted a varied customer base, stressing the need for customized marketing approaches. I also assessed marketing channels, pinpointing email and social media as vital for lead generation but needing optimization for better conversion rates.

The evaluation of the sales team indicated performance disparities, suggesting targeted training could boost efficiency. Additionally, the analysis of operational data spotlighted customer support as an improvement area, especially regarding resolution times and satisfaction levels.

As a project manager for the "Food Aggregator Project," I led a team that significantly advanced the capabilities of our food delivery service platform, ByteBite. I conducted an extensive market analysis and user feedback collection to pinpoint key areas for improvement and innovation. The efforts resulted in the development and integration of several impactful features, including a more intuitive app interface, personalized meal recommendations driven by user history, and a comprehensive loyalty rewards program. I also introduced eco-friendly packaging options and expanded our payment system to include digital wallets and cryptocurrencies, enhancing user convenience and environmental sustainability. My responsibilities encompassed overseeing the technical development, coordinating between different teams, managing the project budget, and ensuring compliance with the latest data protection regulations. The successful launch of these features improved user engagement and satisfaction and positioned ByteBite as a leader in the competitive food delivery market. This project was a testament to our commitment to continuous innovation and user-centric design.