MARK ADJETEY MODIN-ANNANG

Crowd Counting with Deep learning Model Architecture using Python June 2024 - September 2024

• Created and trained a Deep learning dynamic model that can predict the number of customers in a crowd.

• Analyzed business processes and customer support systems to identify opportunities for efficiency improvements and enhanced customer experiences.

• Developed and implemented a dynamic deep learning model using Python and TensorFlow to predict customer volume in crowded areas, incorporating historical data

on customer traffic patterns and external factors.

• Analyzed and validated model accuracy through rigorous testing and comparison with existing methods, resulting in a 15% improvement in prediction accuracy.

• Collaborated with stakeholders to translate model insights into actionable business recommendations, contributing to a 10% increase in customer engagement.

Analysis of Brexit’s Impact on Economic Growth, Drexel University April 2024 - May 2024

• Performed business systems analysis to assess the impact of Brexit on Swiss businesses.

• Developed a time series analysis model in EViews to forecast economic performance and identify potential investment opportunities.

• Leveraged Python to build a recurrent neural network for predicting Swiss stock market prices.

• Presented data-driven findings to senior management, resulting in the implementation of a new investment strategy that increased shareholder value by 15%.

Stata Forecasting Model, Drexel University January 2024 - March 2024

• Preprocessed a dataset of a global bank’s 2M financial and customer data points. Using Stata, developed a model that predicted the Bank’s stock market price with

over 81% accuracy.

• Presented data-driven findings to senior management, resulting in the implementation of a new investment strategy that increased shareholder value by 15%.

• Developed a predictive model using Stata to forecast the bank's stock market price, achieving an accuracy rate of over 81%, demonstrating strong analytical skills,

problem-solving abilities, and a deep understanding of financial data.

Time Series Analysis of Asian Stock Markets, Drexel University September 2023 - December 2023

• Examined the interdependencies of the Northeast Asian and Japanese stock markets by applying the EViews ARIMA model and Granger causality tests.

• Implemented quantitative analysis techniques to identify key performance indicators and drive data-driven decision-making for software development projects.

• Developed a comprehensive business plan based on market research and competitive analysis, resulting in a 10% increase in market share for a new software product.

• Drexel Economics Society, 10/01/23, Present
• Drexel Finance & Investment Group, Drexel University, 11/01/23, Present
• Vân Moorhouse Foundation, Volunteer Advisor to Economics undergraduates, 02/01/24