Aarav Patel

Platform Engineer Intern @ IBM | CS + DS @ Purdue | Prev @ Regions Bank

Chattanooga, Tennessee, United States

About

Experience

  • Platform Engineer Intern at IBM
    May 2026 - Present · 2 mos

  • Software Engineering Consultant at Purdue Solutions Consulting
    Sep 2024 - Present · 1 yr 10 mos

    • Directed development of a non-profit AI transcription platform using FastAPI, OpenAI Whisper, Docker, and AWS Elastic Kubernetes Service, cutting interview review time from 1 hour to 10 minutes for 100+ case managers • Optimized technician routes using Google Maps API, improving route efficiency from 28 to 17 minutes per route • Deployed machine learning underwriting system with FastAPI inference service, containerized with Docker, and hosted on AWS EC2, reducing customer approval times from 3 days to 3 minutes

  • Software Engineer Intern at Syngenta
    Aug 2025 - Dec 2025 · 5 mos

    Built geospatial pipelines in Python, Google Earth Engine, and QGIS to process 5TB of satellite imagery and perform pymannkendall time-series trend detection, reaching 92% precision in cropland degradation detection. Trained scikit-learn models on vegetation and soil data to predict yield variability; regional degradation trends visualized with 3 interactive QGIS dashboards, aiding agronomic resource allocation by 18%.

  • Software Engineer Intern at Regions Bank
    May 2025 - Dec 2025 · 8 mos

    • Engineered AWS-based ETL pipeline with Step Functions and Lambda, processing 10,000+ Jira issues twice daily in under 2 minutes, with infrastructure managed in Terraform and CI/CD automated via Harness. • Loaded Jira data into Snowflake and integrated with Tableau dashboards to automate sprint and KPI reporting, eliminating manual updates of 20+ Gantt charts and saving 30+ teams 10 hours weekly. • Placed first in company-wide AWS Hackathon for building a RAG system in AWS Bedrock indexing 1,000+ Confluence documents, saving 200+ hours by cutting lookup time from 10 minutes to 10 seconds.

  • Undergraduate Researcher at The Data Mine - Purdue University
    Aug 2024 - Aug 2025 · 1 yr 1 mo

    • Conducted data analysis using Python and R within Jupyter Notebooks, examining large-scale datasets to identify patterns and generate actionable insights • Applied statistical modeling, machine learning, and data visualization techniques to uncover trends and support research hypotheses • Collaborated with faculty and fellow researchers to interpret complex datasets • Utilized data visualization tools (e.g., Matplotlib, Seaborn, ggplot2) to communicate findings effectively to both technical and non-technical stakeholders