Oliver Amirmansour

AI & Machine Learning Engineer • Data Analyst • Toronto, ON, CA

Microsoft Azure

Git

Amazon Web Services

Keras

PyTorch

Tensorflow

Deep Learning

Natural Language Processing

Computer Vision

Research

Data Visualization

Data Analysis

Machine Learning

SAS Programming

SQL

Python

Available for hire fromNegotiable

Contracts

Full-Time Roles

Data Science & Finance Professional | ML Research

With a Bachelor of Science in Economics & Business Finance from Brunel University London and a Diploma in Data Science from Lighthouse Labs, I have a strong foundation in both business and data analysis. My experience includes working as an Actuarial & Financial Reporting Analyst at Bupa, where I handled financial reporting tasks. I also conducted research and developed machine learning models for healthcare data analysis at Healthcare Systems R&A Inc. These experiences have honed my skills in data analysis, machine learning, and financial reporting. My educational background and professional experience have equipped me with a unique blend of skills that I am eager to apply in a dynamic and challenging work environment.

Projects

Capstone: Catching Z’s: A Deep Dive into Drowsiness Detection

Tech Stack: YOLOv5, LabelImg, ResNet18, InsightFace, PyTorch, OpenCV, Python. Results: Both models perform well on limited data where the image classification model produces training/validation accuracies of 98.9% and 92.1%. While slight overfitting may be present, more data and tuning will see improvement.See More

Exploring Snow Depth Patterns in B.C. Snow Courses

Tech Stack: Python, Pandas, Numpy, Matplotlib, Seaborn, Statsmodels, Scipy. Results: final model displayed significance across all regressors in predicting snow depth, exhibiting correct signage/direction for all variables, indicating a robust predictive capability.See More

Predictive Modelling for Diabetes Detection

Tech Stack: Pandas, Numpy, Matplotlib, Seaborn and Scikit-learn. Results: Evaluated Logistic Regression and Random Forest models where the latter outperformed in overall performance with a better balance between accuracy and precision, while the former excelled in recall for correctly identifying positive cases.See More

Exploring Urban Dynamics: Bike Station Proximity, Points of Interest, and Predictive Modeling in Tor

Tech Stack: Python, CityBikes API, Foursquare & Yelp APIs, Pandas, Scikit-learn. Results: Positive correlation observed between the number of bars and bike availability and Inverse relationship identified between the number of libraries and bike availability. Model achieved an adj R-squared of 0.116, suggesting the potential for further exploration and the inclusion of additional variables.See More

SQL-Based Data Transformation and Analysis for E-commerce Insights

Tech Stack: PostgreSQL. Results: Regional variation website/user interaction and products ordered by consumers. More than half of websites' revenue attributable to U.S. shoppers.See More

Key Macroeconomic Determinants and Their Effects on London House Prices

Tech Stack: Excel, EViews. Results: Results highlighted a intricate nature of rising London house prices, emphasising heightened demand as a critical component, ultimately contributing to broader picture of macroeconomic influences on the London housing market.See More

Work History

Machine Learning/Data Science Research

Healthcare Systems R&A Inc.Jan 2024 - Mar 2024 • 3 mosResearched and developed computer vision models for emotion classification.

Actuarial & Financial Reporting Analyst

BupaSep 2020 - Aug 2021 • 1 yrHandled actuarial and financial reporting tasks at Bupa.

Education

Lighthouse Labs

Diploma, Data Science, Machine Learning & Data Science2023

Brunel University London

Bachelor of Science - BSc, Economics & Business Finance2018 - 2022

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