Position: Software Engineer | Data Scientist | Data Analyst
Category: Data Science
English level: fluent
Years of experience: 4


Reports and Dashboards using Power BI and Tableau
Analyzed data using Microsoft power bi by creating reports and dashboards of
various datasets such as sales data of products. In these sales data, I created a
sales performance dashboard.
•Through the creation of power Bi dashboards, I wrote DAX expressions to aid in
the analysis of data.
•Created data models which enabled me to connect to different tables in Power
Bi reports. These data models lead to the building of relationships between the
data tables.
•Analyzed data using tableau by creating dashboards to show the trends of data
and get insights from them

Data Analytics On Sales Data
Analyzed sales data using python libraries such as pandas, numpy, sklearn, and
matplotlib for visualizing the data. Derived insights by identifying insights such as
•Products brought together by customers
•Products with high sales volume

House Price Prediction Model
Developed a machine learning model and deployed it using a streamlit python
framework. The model can predict house prices based on certain features such as
the number of bedrooms.

Loan ELigibility Prediction Model
Created a machine learning model using python to predict if a person will default on
a loan payment.

Sentiment Analysis On Movie Reviews
Created a web application system that can be able to distinguish movie reviews as
either positive or negative using a convolutional neural network model. The model
used was through transfer learning. It is a pretrained model developed by google