About Me

I solve problems and tell stories using the most valuable resource on this big blue planet. That resource is, Data. Digesting Data, Finding Patterns, Visualization of Results are just the tip of the iceberg. Using a vast array of Machine Learning tools , I am able to conjure up forecasts that will aid the solution. With that being said , I believe that it is not what you say that matters, it is what people understand that matters.

This project provides a user-friendly web application built with Streamlit to analyze Tesla (TSLA) stock prices and make predictions using various machine learning models.

Projects

This Streamlit project analyzes the sentiments of tweets about US airlines. The application displays visualizations and breakdowns of tweet sentiment, time of day, airline choice, and word cloud for specific sentiments.

This project uses K-means clustering to identify distinct customer segments based on their income and spending patterns. The insights gained can be used to create more effective, personalized marketing campaigns.

This Jupyter Notebook explores analysis and predictive modeling for customer spending in a retail setting. It incorporates data cleaning, feature engineering, and the development of a Linear Regression model for predicting customer spending based on various attributes.

My Journey

Rentoza: Sep 2022 - June 2023

CRM Analyst

My Day to Day Technical Duties included : Designing and building new reports and dashboards, setting up automation for various internal and external processes, and troubleshooting and solving technical issues with the CRM team.

My Day to Day Collaborative Duties included : Setting up new user profiles and managing roles and access according to GDPR/POPIA legislation, managing and reporting on short-term projects, liaising with our Marketing teams to ensure effective leveraging of the CRM platform, and training new and existing CRM users

FxH: Feb 2022 - Feb 2023

Quantitative Analyst

As a Quantitative Analyst at FxH, I had the opportunity to apply my expertise in data analysis to drive business growth and success. In my role, market trends were analyzed, models were built, and trading strategies were developed to generate profits and minimize risks for the company's clients.

One of my key responsibilities was to collect, process, and analyze large amounts of data to identify market trends and opportunities. Valuable insights were uncovered and data-driven trading strategies were developed by leveraging cutting-edge statistical models and machine learning algorithms, which helped our clients achieve their financial goals.

DR Gaming Technology : Feb 2021 - Feb 2022

Sales and Marketing Executive

My duties include Lead Generation (Outbound Calling, Email Marketing Campaigns), Lead Nurturing (Sales Presentations and Demonstrations) and After Sales Services (Upsell and Customer Service).

I had the amazing opportunity to learn (practical and theory knowledge) and work simultaneously in a highly competitive industry such as the Gaming and Accommodations industry.

SearchKings™ Africa : June 2023 - Current

Account Manager

In the world of online advertising, I specialize in managing Google Ads. Using advanced data analysis, I optimize campaigns to get the best results, focusing on improving clicks and conversions. I also use data science to create targeted campaigns that reach the right audience without wasting resources. My work includes predicting budgets and staying updated on market trends. By collaborating with different teams, I contribute to a comprehensive approach to digital advertising.

I'm skilled at creating easy-to-understand reports that help businesses make better decisions. I regularly test and improve ads to make them more effective. I'm passionate about achieving success through a data-driven approach.

Twitch Interactive, Inc : Mar 2019 - Sep 2021

Content Manager

I took care of the content creation of 1-4 hour live streams every weekday, the promotion of the content and the moderation of the project as a whole.

My biggest project was a 24-hour live stream which saw a 280% increase in viewership.

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