Position: Python Developer
Category: Python
English level: upper
Years of experience: 3


Work Experience Summary:

As a software developer, I have gained extensive experience in building web applications using Laravel. Throughout my career, I have had the opportunity to work on a diverse range of projects, each contributing to my growth and expertise in various domains.

One notable project involved conducting A/B tests to analyze and optimize the performance of AD campaigns. This experience allowed me to gain insights into campaign metrics, user behavior, and data-driven decision making. I successfully implemented A/B testing methodologies and contributed to improving the overall effectiveness of the campaigns.

In another project, I worked on topic modeling and causal graph analysis. This involved extracting meaningful topics from large datasets and identifying causal relationships among variables. I leveraged advanced statistical techniques to uncover valuable insights and provide actionable recommendations for decision-making processes.

Furthermore, I had the opportunity to work on Lidar data analysis, where I processed and analyzed Lidar data to extract relevant information and derive insights for various applications. This involved implementing algorithms and techniques to handle complex data structures and derive valuable spatial information.

Additionally, I worked on developing a speech-to-text model specifically designed for the Amharic language. This involved training machine learning models, employing natural language processing techniques, and fine-tuning the system to accurately transcribe Amharic speech into text.

Moreover, I worked as a big data analyst at Huawei for one year. In this role, I was involved in analyzing large-scale datasets, implementing data processing pipelines, and deriving actionable insights from the data. This experience provided me with valuable exposure to big data technologies and enhanced my skills in data analysis on a larger scale.

In the field of sales prediction and time series analysis, I applied statistical modeling and machine learning techniques to predict pharmacy sales. By analyzing historical sales data and incorporating relevant factors, I was able to build accurate forecasting models that supported effective inventory management and business planning.