• Developed and delivered structured lectures, using interactive teaching methods to enhance the students' engagement and comprehension.
• Created and assessed evaluations, providing targeted feedback to ensure each student knew what to work on to improve their grade.

• Taught mathematical concepts to 100 students with diverse academic backgrounds while ensuring their comprehension and engagement.
• Collaborated with professors and students to address challenging topics and improve overall class understanding.

-I thoroughly studied the insurance contracts of dozens of corporate clients, allowing me to evaluate beneficiaries' medical conditions efficiently and precisely. This also gave me the knowledge to provide accurate and informed responses to a diverse clientele regarding personal and complex situations.
-Exceeded the average daily call quota while maintaining a call time average below 6 minutes.

-Collaborated with professors to grade assignments and exams, ensuring fair evaluation and feedback.
-Prepared and delivered weekly review sessions, which helped over 50 students grasp the material.
-Identified and addressed common difficulties for specific students. This led to an increase of the students' comprehension and performance in challenging topics.

-Worked on a project developing a labeling tool for web pages, improving web navigation for visually impaired users.
-Utilized Bayesian statistics and Hidden Markov Trees to develop probability models in Python, enhancing the predictive accuracy of our model.

-Developed a statistical analysis program using Matlab which reduced the data analysis process to a few seconds .
-Cleaned and prepared data related to provincial rain levels, ensuring accuracy for subsequent analyses.
-Employed mathematical concepts such as linear algebra and integration,to optimize the program

-Assisted professors in grading assignments and exams, maintaining a high standard of accuracy and fairness.
-Communicated complex mathematical concepts to students of varying proficiency levels, improving class comprehension.
-Created custom practice problems, enhancing understanding of key concepts for struggling students.

-Developed an algorithm to identify duplicate subtrees within a webpage's DOM tree, which was then used to Identify common patterns on the web.
-Translated web page's DOM tree into Python objects, which improved the data extraction and manipulation processes

-Conducted 15-60 minute interviews with households nationwide, contributing to a comprehensive 2021 Census.
-Collected and processed data, ensuring an accurate representation of diverse demographic profiles.
-Exceeded daily interview targets despite challenges such as language barriers and customer dissatisfaction.

Managed the social media account for MAGMA(The Multicultural Agency of the Greater Moncton Area). Created original content and curated a content calendar that allowed for a brand new account to reach 1000 followers in 4 weeks.

Developed a generative Machine Learning model (Variational Auto-Encoder) in Python and applied it to fitted Geometric Brownian Motion parameters. This led to the production of realistic stock price scenarios validated with histograms and Wasserstein distances.

Analyzed the impact of BMI on wages using the NLSY79 panel data, employing both OLS and
Two-Stage Least Squares (2SLS) models. Additionally, an instrumental variable (BMI in 1981) was used to
address endogeneity. We controlled for factors like education, mental health, and discrimination, and conducted
subanalyses by gender and ethnicity to see which group’s wages were most affected by BMI

Developed a neural network that classifies handwritten digits (0–9) using the MNIST dataset, achieving 96.72% accuracy. The model learns to recognize patterns in pixel values and distinguishes digits through supervised learning.