Akunna Anyamkpa

I am a tech- creative with 3 years of experience in data cleaning, data gathering, data analysis, data visualization, and building machine learning models using data. Over time, I have been opportune to work on sales, leads, financial, and management dashboards as requested. 

At layer 3, I was a part of the team that managed, optimized, and built on the management and sales dashboards. I also worked with the engineering department to build the customer response dashboard to capture important Key performance indicators like churn rate. The dashboards were all built and managed on google sheets using pivot tables and charts respectively.

In 2022, I engaged in building a business analytics system for a Nigerian-based startup and Us based NGO. The business analytical systems were built and managed using google data studio, google sheets, and google forms for data visualization, data gathering, data manipulation, and data collection respectively. The business analytical system conveyed information on Budget, Finance, Expenses, Sales, Leads, Company Staff, and employment details. 

The first model I built using Python was aimed at predicting the price of cars based on the features inputted into the model. I used linear regression, Decision tree regression, and random forest regression libraries to build the model. The highest model evaluation accuracy score read 96 percent which was impressive.

Later on, I engaged in some projects I found on Kaggle like building a water quality prediction model which was based on classification problems. Then I took up a project where I used K-means clustering to group customers who often purchase from a mall based on their buying patterns.

I engaged in virtual internships where I worked on real-life Data science scenario projects with British Airways and Cognizant AI teams. I learned how to build models that solve their problem by predicting if the customer will book with British Airways based on some correlating features. I learned how to scrape from the web using beautiful-soup and also used word clouds to detect the most recurring complaint or topic from a group of texts. At Cognizant, I was opportune to practice and learn how to derive insights from the provided data using Python for exploratory data analysis and predicting the estimated stock levels.

I have improved and developed my hard and soft skills like teamwork, problem-solving, presentation, critical thinking, time management, leadership, communication, and stress management.