Hi, my name is Abbas Meghani
I am a Software Engineer with experience in data-intensive backends and Machine Learning research.

About Me


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Education

Experience

Projects

Research

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About me

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I am a Software Engineer with experience working in an intensive startup environment alongside an AGILE team. I have more than three years of experience in object-oriented programming, particularly in the development of high-volume, low-latency projects. My professional track record highlights my proficiency in tackling intricate data-intensive applications, with a keen focus on optimizing efficiency.

Outside of my professional commitments, I enjoy going on long hikes in nature, reading books and having a warm cup of tea.

View Resume

Education

MSc: Data Science

at HEC Montréal, University of Montréal

Website

GPA: 3.6

Notable Achievements: Received a scholarship for Fin-ML Research and was hired three times for distinct programming projects, two of which were used to facilitate course capstone projects.

Coursework: Decision Analysis, Machine Learning, Machine Learning II: Deep Learning, Adv. Statistics, Forecasting Methods, Algorithms, Complex Networks Analysis, Optimization, Statistical Modelling

BEng: Computer Engineering

at Rizvi College Of Engineering (RCOE), University of Mumbai

Website

GPA: 8.4

Notable Achievement: One of only two teams in my cohort to receive research funding for the engineering capstone project.

Coursework: Data Structures, Object Oriented Programming, Data Management Systems, Distributed Systems, Operating Systems, Adv. Applied Mathematics I/ II/ III/ IV, Digital Logic Design, Microprocessor, Circuits, Web Technologies

Experience

Apr 2024 – Present

Sr Applied Data Scientist — Backend & Data Infrastructure

Feb 2022 – Apr 2024

Applied Data Scientist — Backend & Data Infrastructure

at Shift-Technology, a Fintech Unicorn Startup

Tech Stack: C#, Python, SQL, ElasticSearch, Docker, GCP Cloud Run, AWS
CI/ CD: TeamCity, Octopus, GitHub Actions

Website

  • Led ORM redesign reducing data extraction time by 20%, improving backend scalability across all client environments.

  • Integrated ElasticSearch API into the fraud detection backend, enabling high-performance entity search at scale.

  • Built a factory-based data transformation library in C#/.NET supporting 15+ enterprise clients with minimal per-client config.

  • Refactored the ML microservices data transformation layer, delivering a 5% company-wide processing efficiency gain.

  • Coded hash-based deduplication filters to efficiently ingest and process tables with up to 9 billion highly duplicated rows within server memory constraints.

June 2021 – Feb 2022

Software Engineer — Backend

at DocuFire

Tech Stack: C#, .NET Core, SQL
CI/ CD: Windows Installer, InstallShield

Website

  • Increased document generation throughput by 15% via async parallel processing of pages in the PDF generation module of the core ERP system.

  • Migrated legacy data access layer to a REST API with full unit test coverage, preserving all existing endpoints and strengthening system reliability.

  • Designed and developed the MVC backend for an ASP.NET Core web application, seamlessly integrating it with the REST API.

May 2021 – Oct 2023 (Part Time)

Research Assistant — Backend & ML Systems

at HEC Montréal, University of Montréal

Tech Stack: C#, ASP.NET Core, MySQL, Python

Website

  • Built a scalable ASP.NET Core web app with MySQL for the 'Sports Analytics' course, including user registration, team and game sign-ups, and an on-server ML model simulating sports game outcomes.

  • Developed Python visualizations for a sports simulation ML model, subsequently adapting them for use on the server.

Aug 2021 – Oct 2021 (Part Time)

Research Consultant

at Sentometrics, writing a Machine Learning research paper

Tech Stack: R, Python

Website Publication

  • Used topic modeling (R) to analyze and gain insights about financial research over time.

  • Scraped data, preprocessed text, and annotated the text corpus.

  • Created and transformed several covariates for 33 Financial Journals.

  • Implemented, optimized, and compared multiple Structural Topic Models for relevant insights.

Sept 2020 – Apr 2021 (Part Time)

Research Assistant

at ERPSim Lab, HEC Montréal

Tech Stack: Python, SAS

Website

  • Documenting and verifying validity (Python) of simulated data for use in Cortex - a platform for learning and practicing data science concepts.

  • Programming in SAS and writing guides for students and teachers about using SAS-EM effectively to analyze the simulated datasets.

Projects

Apr 2021 (Python)

Complex Networks

  • Created a complex road network of bike sharing service usage by overlaying it with a road network of the city.

  • Converted data into daily and weekly demand time series and incorporated conversion of time series data into complex networks using distance metrics and also a visibility graph.

  • Analyzed networks using global/local network descriptors, & community detection algorithms.

Report
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Oct 2020 (Python)

Convex Hull Algorithms

  • The project features a GUI for visualizing convex hull algorithms using Python & Tkinter.

  • Users can explore algorithms like Brute Force, Jarvis' March, Graham Scan, and Divide & Conquer by generating random points.

  • A specialized LeftHull algorithm is included for polygon convex hulls.

  • These algorithms are implemented from the psuedocode in their original research papers, wherever available.

See Code
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Nov 2019 (Python)

Convolutional Neural Networks

We classify images of recyclable trash into different categories by using the following:

  • Support Vector Machines (SVM): One vs Many

  • Convolutional Neural Networks (CNN):

    • Architectures: VGG10, VGG13, VGG16, ResNet34

    • Hyperparameters: Pooling, Batch Normalization, Depth, Data Augmentation

Poster
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Research

Jun 2023 (R, Python)

Thirty years of academic finance

in The Journal Of Economic Surveys

Employed an unsupervised Machine Learning Bayesian Model, the Structural Topic Model, to analyze financial journals.

Paper
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May 2018 (Java)

Wearable Navigation and Assistive System for Visually Impaired

in the 2nd International Conference on Trends in Electronics and Informatics, published by IEEE

Developed an Arduino project integrating ultrasonic sound sensors and a gyroscope onto a glove, accompanied by custom code aimed at enhancing navigation for individuals with visual impairments.

Paper
Project Image

Dec 2017 (Java, Android Studio)

Intelligent disaster warning and response system with dynamic route selection for evacuation

in the 2017 International Conference on Intelligent Sustainable Systems, published by IEEE

Created an Android application designed to issue natural disaster warnings and guide users to the closest warehouse, factoring in considerations such as distance, capacity, and other relevant metrics.

Paper
Project Image

Oct 2017 (PHP, HTML, CSS)

Multi-platform college management framework

in the 2017 2nd International Conference on Communication and Electronics Systems, published by IEEE

This project entails the development of a web application aimed at modernizing and optimizing record management processes in colleges and universities. By digitizing these tasks, it effectively lessens the administrative burden. The application encompasses features such as an online paper-checking module, attendance tracking, and a digital notice board, all of which contribute to enhanced efficiency in academic operations.

Paper
Project Image

Contact Me

Toronto, Ontario, Canada

Number: +1 (438) 866-6499

Email: abbmeghani@gmail.com

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