About Me

I'm Titilayo Amuwo, a versatile professional with a background spanning Financial analysis, Data science and Software engineering. I embarked on a career transition journey from the Financial industry to the field of Data science where I developed a comprehensive understanding of data analytics and machine learning. During this transition, I honed my skills as an innovator exploring dataset, developing and optimizing machine learning models to help businesses make an informed decision. I trust the power of collaboration and continuous learning, that is why throughout my career, I collaborated with cross-functional teams to deliver impactful solutions and drive organizational success. My commitment to excellence, and passion for innovation have led to notable achievements, including developing predictive analytics models that reduced forecasting errors by 15% and increased efficiency by 20%. In today’s fast-paced and interconnected world, I am excited to continue leveraging my unique skills to contribute value to companies at the intersection of data, and technology. Whether it is optimizing machine learning algorithm, harnessing the power of data to drive business insights, or implementing cutting edge technology solutions, I'm dedicated to making a meaningful impact.


Let’s connect and explore how we can work together to turn ideas into reality!

  • Technical Tools
  • Python
  • Java
  • SQL
  • Data Analytics and Machine Learning Tools
  • Web Development Framework
  • Skills
  • Team-work
  • Communication
  • Inference
  • Problem-solving
  • Analytical thinking
  • Data Mining
  • Machine learning
  • Artificial Intelligence
  • Financial Analysis and Reporting
  • Market Research and Analysis
  • Software Development
  • Statistical Analysis
  • June 2024 - Present
    Data Center Operation Technician II at Amazon
  • February 2022 - June 2024
    Machine Learning Engineer at Omdena
  • February 2023 - August 2023
    Information Technology Intern at Rubric
  • June 2022 - November 2022
    Political Technical Specialist at Zinc Collective
  • August 2021 - December 2021
    Data science student at Flatiron School
  • July 2020 - August 2021
    Accounting Bookkeeper at Intuit
  • June 2020 - April 2021
    Staff Accountant at The Mercury Group
  • February 2018 - June 2020
    Accounting Clerk at Penske Automotive Group
  • Present
    BSc - Information Technology, Software Development from Purdue University Global
  • 2019
    BSc - Accounting from University of Bridgeport
  • 2021
    Technical Certificate - Data Science from Flatiron School
  • Flatiron

  • Oct. 2023
    Getting started with Networking from AWS
  • Oct. 2023
    Web Application Development Builder from AWS
  • Sept. 2023
    AWS Machine Learning Fundamentals from Udacity
  • Udacity

  • Oct. 2022
    AWS AI Programming with Python from Udacity
  • Udacity

  • Sept. 2022
    Diagramming Foundations from Lucid
  • Apr. 2022
    Certified Cloud Practitioner from AWS
  • Dec. 2021
    Master SQL for Data Science from Udemy
  • Udemy

Projects

Soccer Match Betting

In this project, I employed a methodology that integrates various machine learning algorithms to develop a soccer forecasting model. The model predicts match outcomes based on a power index, historical performance, and odds data.

Landmark Tagging for Social Media

In this project, I developed a Convolutional Neural Network (CNN) algorithm and an accompanying application capable of accepting landmark images and predicting their locations.

Scone Unlimited Image Classification

In this project, I implemented a deep learning approach using AWS SageMaker to classify images, with the objective of developing a scalable and reliable model capable of distinguishing bicycles from motorcycles.

City Bike-Sharing Systems

In this project, I applied a range of machine learning algorithms on AWS SageMaker to forecast the usage patterns of bike-sharing systems in Washington, DC.

Data Analysis using Tableau

In this project, I leveraged publicly available data to create visualizations in Tableau Public for analysis and generating insights.

Flower Classification

In this project, I implemented a transfer learning approach using the VGG16_bn pretrained model to train a dataset of flower categories. The resulting model was then utilized to develop a command-line application capable of predicting flower categories.

Women In Data Science Datathon

In this project, I have employed various machine learning algorithms to predict the site energy usage intensity of buildings based on their characteristics and location-specific weather data.

Learn more

Blogs

Tableau: Do you really need it? this tutorial will help you decide.

Learn more

A summary of Data science and AI in finTech with examples of how it is used.

Learn more

A short tutorial on timeseries forecasting with Facebook Prophet.

Learn more

Contact

titilayo@abbyamuwo.com

Download Resume