Hi! I'm Fardil
Data Analyst │ Junior Data Scientist
Analyzing and visualizing data to make better and informed business decisions.
Fardil Bhugaloo
Analyzing and visualizing data to make better and informed business decisions.
About Me
“The goal is to turn data into information, and information into insight.” - Carly Fiorina
I am a data analyst with a background in insurance and also in retail industry, with the curiosity and imagination to make connections between different data sets, draw conclusions and turn problems into solutions. With my passion for making a sense of information, and turning data into knowledge, I retrained as a data analyst to improve my skills and be able to make sense of larger-scale data sets. I am currently in my last few modules to complete my Master’s in Applied Data Science & AI from DSTI. I already have a bachelor in Business and a master in Finance.
I am skilled in collecting and manipulating data, designing, and testing hypothesis, creating predictive models and storytelling about the findings. I thrive in fast-paced, and goal-oriented environments with dedicated teams as well as working independently. I am passionate about simplifying problematic and complex business questions, ideas, and real-life scenarios, using analytical skills.
Currently: Learning TensorFlow for building deep learning models and AWS for deploying machine learning models in the cloud.
Portfolio
Rockbuster Stealth Data Analysis
A performance analysis done to help a movie rental company launch an online rental service to stay competitive.
Tools: PostgresSQL, Microsoft Excel, Tableau
Instacart Grocery Basket Analysis
The goal of the analysis was to perform an initial data exploratory analysis to derive insights and suggest strategies for better segmentation of Instacart shoppers.
Tools: Python
Preparing for Influenza Season
The analysis aimed to plan the distribution of medical staff across the U.S. countries to prepare for the influenza season using datasets from the U.S. Census Bureau and CDC.
Tools: Microsoft Excel, Tableau
ML Project: Rental Apartment in Germany Prices Analysis
The goal of this project was to find any useful insight regarding the rental apartment in Germany. Regression was used to predict rental prices and K-Means was applied to identify clusters within the dataset.
Tools: Python
ML Project: Customer Segmentation Arvato Bertelsmann
In this project, I used unsupervised learning techniques to perform customer segmentation, identifying the parts of the population that best describe the core customer base of the company. Then, I applied what I have learned on a third dataset with demographic information for targets of a marketing campaign and use a model to predict which individuals are most likely to convert into becoming customers for the company.
Tools: Python