Summary
Overview
Work History
Education
Skills
Timeline
Projects
Work Preference
References
JAY PANDYA
Open To Work

JAY PANDYA

Mississauga,Ontario

Summary

Detail-oriented Data Analyst with a strong foundation in Computer Science, Cloud Computing, and Artificial Intelligence. Proven ability to transform complex datasets into actionable insights through advanced analytics, machine learning, and interactive dashboards. Skilled in SQL, Power BI, Python, and cloud platforms (AWS, Azure, GCP). Recognized for analytical problem-solving, collaborative teamwork, and delivering measurable results in industry-sponsored projects.

Overview

1
1
year of professional experience

Work History

AI ML - INTERN

Thinkswift
Toronto, Ontario
05.2025 - 08.2025
  • Developed AI-powered scoring platform through implementation of machine learning and deep learning models.
  • Engineered features and established data pipelines to enhance model performance.
  • Gained hands-on experience with Azure ML, AKS, and data versioning in Blob Storage.
  • Collaborated with cross-functional teams to deliver scalable, production-ready machine learning solutions.

Cloud Engineer - INTERN

Cloudsolutions Zone
Toronto, Ontario
05.2024 - 08.2024
  • Developed AWS QuickSight dashboard to visualize multi-account cost and usage data, uncovering estimated savings of 10–15%.
  • Collaborated with industry client to provide insights enhancing cloud cost governance and operational efficiency.

Education

PG DIPLOMA - Artificial Intelligence With Machine Learning

Humber College, Toronto
08-2025

PG DIPLOMA - CLOUD COMPUTING

Humber College, Toronto
08-2024

Bachelor - Computer Engineering

LDRP ITR, Ahmedabad
08-2023

Skills

  • Business Intelligence & SQL: Power BI, AWS QuickSight, Excel, SQL
  • Big Data & ETL: PySpark, Hadoop, ETL development; JSONL data handling
  • ML & Analytics: Python, feature engineering, statistical analysis, NLP; model evaluation
  • Cloud & DevOps: AWS, Azure, GCP; Docker, Kubernetes; Terraform, Ansible
  • Streaming & Observability: ELK Stack (Elasticsearch, Logstash, Kibana); GCP Cloud Storage metrics; near-real-time pipelines
  • Ways of Working: Agile/Scrum, data analysis, machine learning, cloud computing

Timeline

AI ML - INTERN - Thinkswift
05.2025 - 08.2025
Cloud Engineer - INTERN - Cloudsolutions Zone
05.2024 - 08.2024
Humber College - PG DIPLOMA, Artificial Intelligence With Machine Learning
Humber College - PG DIPLOMA, CLOUD COMPUTING
LDRP ITR - Bachelor, Computer Engineering

Projects

Capstone Project

  • Cost Intelligence Dashboard for AWS Accounts, Collaborated with an industrial client to develop a comprehensive dashboard that provides actionable insights into AWS cost management using AWS QuickSight.
  • Presented the project at the Capstone Expo, honing skills in cloud computing, data analytics, and effective teamwork while fulfilling industry requirements.

Prevision360

  • AI-Powered Startup Scoring Platform - Led data and ML development for a scoring platform analyzing milestone records with number of engineered features, including sentiment and culture mix.
  • Designed an unsupervised BiLSTM Autoencoder producing 0–100 performance scores; improved interpretability via feature/timestamp deltas and narrative insights. Deployed on Azure (ML, AKS, ACR) with versioned datasets in Blob Storage; delivered both batch and real-time pipelines.
  • Built a Power BI dashboard for KPI tracking, industry funnels, and peer benchmarking.

Amazon Books Sentiment Classification with PySpark & ELK (GCP)

  • Developed a multiclass sentiment classifier (Negative/Neutral/Positive) on 30M+ Amazon reviews using PySpark with Logistic Regression.
  • Built a streaming pipeline (Logstash → Elasticsearch → Kibana) integrated with GCP Cloud Storage, enabling real-time monitoring and dashboards.
  • Enhanced decision workflows with top-K analysis and probability calibration, proposing improvements for Neutral-class accuracy.
  • Delivered a scalable, near real-time analytics platform for large-scale JSONL review data.

Work Preference

Work Type

Full TimeContract Work

Location Preference

HybridOn-SiteRemote

References

References available upon request.

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JAY PANDYA