I'm a Computer Science graduate with nearly 2 years of experience across internship and part-time software development roles. I have shipped full-stack products and integrated AI-powered workflows through backend automation, API-driven services, and cloud platforms. I excel at translating product ideas into scalable web applications with modern frontend, backend, and data-driven system design, and I enjoy collaborating with designers, product managers, and stakeholders in Agile teams to deliver production-ready solutions.…

Ansh Malhotra

I'm a Computer Science graduate with nearly 2 years of experience across internship and part-time software development roles. I have shipped full-stack products and integrated AI-powered workflows through backend automation, API-driven services, and cloud platforms. I excel at translating product ideas into scalable web applications with modern frontend, backend, and data-driven system design, and I enjoy collaborating with designers, product managers, and stakeholders in Agile teams to deliver production-ready solutions.…

Available to hire

I’m a Computer Science graduate with nearly 2 years of experience across internship and part-time software development roles. I have shipped full-stack products and integrated AI-powered workflows through backend automation, API-driven services, and cloud platforms.

I excel at translating product ideas into scalable web applications with modern frontend, backend, and data-driven system design, and I enjoy collaborating with designers, product managers, and stakeholders in Agile teams to deliver production-ready solutions.

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Skills

Experience Level

TypeScript
Expert
React JS
Expert
Python
Expert
JavaScript
Expert
SQL
Expert
Django
Expert
HTML5
Expert
Java
Expert
PostgreSQL
Expert
Jira
Expert
Docker
Expert
CSS
Expert
bash
Expert
Azure
Expert
AWS
Expert
C++
Intermediate
Tailwind
Intermediate
Prompt Engineering
Intermediate
AngularJS
Intermediate
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Language

Javanese
Advanced

Work Experience

Full Stack Web Developer Intern at University of Toronto
September 1, 2023 - December 1, 2024
Delivered secure, multi-step onboarding workflows for 200+ users using modular React + Firebase, improving data reliability and repeat engagement. Increased real-time program visibility by designing reusable backend data models and aggregation pipelines that transformed raw survey inputs into structured analytics (mood, stress, trend metrics), enabling stakeholders to monitor engagement across hundreds of student submissions. Collaborated cross-functionally in Agile sprints with designers and stakeholders to translate requirements into maintainable, production-ready full-stack solutions.
Cloud Engineer Intern at Rogers Communications Inc.
May 1, 2023 - August 1, 2023
Improved and supported 5+ cloud-based services (VMs, Cosmos DB, AKS, Azure ML, Azure Bots) using Azure DevOps by contributing to CI/CD automation and build pipelines, improving deployment consistency across development and staging environments. Resolved 15+ deployment and configuration issues across multiple environments by troubleshooting Azure-based services, reducing release delays and improving system stability. Supported 10+ Azure PCRS cost estimation models by analyzing High-Level Design Documents and validating infrastructure assumptions, improving budgeting accuracy.

Education

Honours Bachelor of Science (BSc), Specialization in Computer Science at University of Toronto
September 1, 2020 - May 1, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Education, Computers & Electronics, Telecommunications
    paper NFL Predictor

    NFL Predictor is an ensemble prediction system that combines multiple data sources and analytical agents to forecast NFL game outcomes. The system is built on a FastAPI backend and React frontend, deployed on Railway.
    It uses a multi-agent architecture with four specialized components:

    Stats Agent — pulls historical and current team performance data from the ESPN API
    Weather Impact Agent — factors in game-day conditions (wind, precipitation, temperature) with uncertainty quantification and abstention logic for low-confidence forecasts
    News Sentiment Agent — applies NLP to analyze recent team news, injury reports, and media sentiment
    Market Intelligence Agent — incorporates betting lines and Vegas spreads as a signal of collective expert wisdom

    Predictions from all four agents are weighted and aggregated into a final ensemble forecast, achieving a reported ~74.7% accuracy across three weeks of live testing.