JS.

Toronto, Ontario

Jainam Shah

Computer Science Co-op student at Toronto Metropolitan University.

Interested in software, security, and machine learning.

Experience

Work & research

  1. Junior Software Developer (Co-op)incomingCGIMarkham, OntarioStarts Jan 2027
  2. Software EngineercurrentBEACON Research Group · Toronto Metropolitan UniversityToronto, OntarioMay 2026 – Present
    • Developed Python microservices for a Kafka-based smart-building platform, processing real-time sensor data for analytics and machine-learning workflows.
    • Built Kafka-to-PostgreSQL ingestion services using SQLAlchemy, automating database schema initialization and persisting telemetry and analytics metadata.
    • Containerized and integrated backend services with Docker Compose within an 11 - microservice architecture.

    Python · Apache Kafka · PostgreSQL · SQLAlchemy · Docker Compose · Git

    Visit organization
  3. Security Operations Center (SOC) AnalystOntario Power GenerationToronto, OntarioSep 2025 – Apr 2026
    • Investigated 50+ phishing reports weekly using Cofense Reporter, Microsoft Defender, VirusTotal, and Microsoft Sentinel to identify malicious indicators and assess organizational risk.
    • Correlated and enriched hundreds of indicators of compromise (IOCs) using threat intelligence sources, Splunk, and KQL, documenting findings and tracking security incidents through ServiceNow.
    • Built Python scripts to automate IOC parsing, normalization, and reputation lookups, reducing repetitive triage effort by approximately 30%.
    • Provisioned privileged accounts using CyberArk, supporting secure access management and administrative access controls.

    Microsoft Sentinel · Microsoft Defender · Cofense Reporter · Splunk · KQL · Python · VirusTotal · Wireshark · CyberArk · ServiceNow · Microsoft Office

  4. Research AssistantCybersecurity Research Lab · Toronto Metropolitan UniversityToronto, OntarioMay 2024 – Aug 2025
    • Built 8 Python web scrapers with Selenium, Pandas, and NumPy to collect, clean, and structure data from Twitter/X, GitHub, and Google News for research analysis.
    • Developed NLP preprocessing pipelines using spaCy and NLTK to clean, normalize, and prepare large text datasets for analysis.
    • Applied existing machine learning and NLP models to processed datasets to identify patterns, extract research insights, and visualize findings with Matplotlib.
    • Automated internal workflows using JavaScript and Google Apps Script, reducing manual effort by 70% and improving data reliability.

    Python · JavaScript · scikit-learn · PyTorch · Hugging Face Transformers · Git · GitHub · Google Apps Script

    Visit organization

Projects

Selected work

Algoware

A Chrome extension that makes YouTube recommendations easier to understand through topic and sentiment analysis.

  • Led a four-person team, using Manifest V3 content scripts and service workers to coordinate inference and visualize results.
  • Built a Flask API with a fine-tuned BERT model for 26-class topic classification and Google Cloud Natural Language for sentiment analysis.

Python · Flask · PyTorch · BERT · JavaScript · HTML/CSS

Source Devpost

Lumina

A real-time collaborative drawing application with shared strokes, live cursors, and presence awareness.

  • Synchronizes drawing events and user presence for up to 200 concurrent users.
  • Built with Next.js, TypeScript, and Supabase Realtime and Auth.

Next.js · TypeScript · Supabase · Tailwind CSS

Source Live site

Earlier projects

Skincare Recommender

Python-based application helping users find skincare products tailored to their skin type, budget, and preferences using graph-based recommendations.

  • Graph data structure with users/products as nodes and 8000+ reviews as edges
  • Interactive Tkinter GUI with real-time filtering by skin type, budget, and brand

Python · Pandas · Tkinter

Source

Citco

Web application investigating correlation between individual researchers' citation counts and NSERC Discovery Grant funding amounts.

  • Web-scraped dataset from NSERC grant database and Google Scholar citations
  • Statistical analysis revealing Pearson correlation coefficient of ~0.3

Python · Pandas · NumPy · Matplotlib · Flask

Source

NewsNest

MERN stack news aggregation platform allowing users to explore, save, and manage articles with JWT authentication and NewsAPI integration.

  • RESTful API with Express backend and MongoDB for user authentication
  • Keyword search functionality with personalized article saving and management

Node.js · Express · React · MongoDB

Source

Education & skills

Toronto Metropolitan University

B.Sc. (Hons) in Computer Science, Co-op

Expected Apr 2028

CGPA 3.97 / 4.33

Coursework Data Structures & Algorithms · Artificial Intelligence I · Discrete Mathematics

Languages
Python, Java, JavaScript, TypeScript, SQL, C/C++, Bash, HTML/CSS
Frameworks & libraries
React, Next.js, Flask, SQLAlchemy, PyTorch, Hugging Face Transformers, scikit-learn, Pandas, NumPy, spaCy, NLTK, Selenium
Tools & platforms
Git, GitHub, Docker, Kafka, PostgreSQL, Linux/Unix, Supabase, MySQL, MongoDB, AWS, Jupyter Notebook, Power BI, Vercel

Get in touch

Have something in mind? I’d be happy to hear from you.

j9shah@torontomu.ca