Frank Kyei Baffour

A certified Data Scientist with professional experience in building Machine Learning Models and Exploratory Data Analysis. I am capable of creating, developing, testing and deploying highly adaptive and diverse business intelligence solutions.

I am looking for the opportunity to build a challenging career and apply my skills in an innovative and simplify process. I enjoy working in a team and communicating data driven results.

 1.  Indian-Start-up-Funding-Analysis 

• An in-depth analysis on the funding received by start-ups in India from 2018 to 2021 was carried out using python Libraries like Pandas, Matplotlib, Seaborn, Numpy.

2.  Regression Project (Store SalesTime Series Forecasting)

• In this project, I performed an EDA and built a Regression Model that predicts the sales for product families sold at Favorita stores located in Ecuador.

3.  Classification-Project (Predicting-Customer-Churn)

• The aim of this project was to find the likelihood of a customer leaving a telecom organization, the key indicators of churn as well as the retention strategies that can be implemented to avert this problem. An EDA and a classification model was built to predict customer churn.

4.  Streamlit-App-for-ML-Model-Project

• In this project, I used streamlit to build a web App with a user-friendly interface to embed my ML model from Sales Forecasting Project.

5.  Gradio-App-for-ML-Project

• In this project, I used gradio to build a web App with a user-friendly interface to embed my ML model from Customer Churn Prediction Project.

6.   Sentiment-Analysis-Project (Deep-Learning)

• This was an NLP Live Project based on the Zindi's challenge. I finetuned a pretrain Hugging Face model to assess if a Twitter post related to vaccinations is positive, neutral, or negative, and built a Gradio App to test model on huggingface.

7.  Titanic-Project (Machine-Learning-from-Disaster)

• The aim of this project was to create an API that might be requested to interact with a ML model. I perform an EDA and developed a Classification model to predict passenger survival. After that I built a ML API, and streamlit App to interact with the Model.

8.  Customer-Churn-Prediction for Expresso

• This projet was based on a Zindi challenge for an African telecommunications company(Expresso) that provides customers with airtime and mobile data bundles. The objective was to develop a machine learning model to predict the likelihood of each customer “churning,” i.e. becoming inactive and not making any transactions for 90 days. A fine-tuned predictive model, a web app and API was built in this project.

• Certified Business Analyst ( SCALEWORK & Azubi Africa)
• Organizational Skills ( Ahaspora Professionals Network )
• Certified Regional Trainer (Ghana Statistical Services)
• Public Health Emergency Operations-Logistics Series ( Africa CDC )