Dev Gandhi

Product Manager

Chapel Hill, North Carolina, United States1 yr 11 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Designed a log analytics system reducing incident response time by 40%.
Led a business intelligence team achieving 92% forecast accuracy.
Automated IT asset tracking, optimizing data retrieval by 25%.

Stackforce AI infers this person is a Data Science and AI professional with a focus on system optimization and analytics.

Contact

gandhidev36@yahoo.com LinkedIn

Skills

Core Skills

Data ScienceData AnalysisSystem AdministrationData Engineering

Other Skills

Python (Programming Language)Algorithm DesignSQLTechnical SupportDesign ThinkingSplunkLinuxMySQLLean Six SigmaBusiness Process ImprovementService WorkFood Service OperationsCustomer ServiceCommunicationPublic Relations

About

Currently contributing as an Artificial Intelligence Engineer Intern at IRI-Sys while pursuing a Master of Library & Information Science at the University of North Carolina at Chapel Hill. With a focus on leveraging data-driven strategies, past roles include designing log analytics systems with Splunk and automating IT asset tracking at UNC SILS Technology. Committed to empowering organizations through innovative AI and data science solutions, including streamlining processes, optimizing system performance, and enhancing security protocols. Motivated by the intersection of technology and business improvement, and driven to deliver impactful, collaborative results.

Experience

1 yr 11 mos

Total Experience

11 mos

Average Tenure

Current Experience

Pathfinder oncology

Solutions Architect Intern

Aug 2025 – Present · 9 mos · Chapel Hill, North Carolina, United States · Hybrid

Unc school of data science and society

AI/AP Fellow

Aug 2025 – Present · 9 mos · Chapel Hill, North Carolina, United States · Hybrid

Unc school of information and library science

Machine Learning Research Intern

May 2025 – Dec 2025 · 7 mos · Chapel Hill, North Carolina, United States · Hybrid

Iri-sys

Artificial Intelligence Engineer Intern

May 2025 – Aug 2025 · 3 mos · Chapel Hill, North Carolina, United States

Renaissance computing institute

Data Science Intern

Jan 2025 – May 2025 · 4 mos · Chapel Hill, North Carolina, United States · Hybrid

Python (Programming Language)Algorithm DesignData Science

Unc school of information and library science

Carolina Technology Associate

Aug 2024 – Dec 2024 · 4 mos · Chapel Hill, North Carolina, United States · On-site

Designed and implemented a Splunk-based log analytics system for monitoring classroom IT infrastructure and school hosted servers, centralizing logs, building real-time alerting for security events and outages, and creating dashboards that reduced incident response time by 40%.
Deployed and managed a Linux-based server for Snipe-IT, automating IT asset tracking with MySQL database integration, optimizing data retrieval by 25%, and ensuring 99.9% system uptime.
Automated server maintenance and security monitoring, implementing firewall rules, access controls, and shell scripts for updates and backups, reducing manual effort by 50%.

Technical SupportDesign ThinkingSystem Administration

Findingpi

2 roles

Associate Data Scientist

Jul 2023 – Jul 2024 · 1 yr · Nagpur, Maharashtra, India

Led a business intelligence team of 4 interns to build Tableau dashboards integrating behavioral analytics and Prophet-based forecasting models for ticket sales and user engagement KPIs. Achieved 92% forecast accuracy, enabled dynamic pricing and campaign automation, and drove an 18% increase in revenue
Designed and deployed an enterprise data intelligence portal for Cornerstone Auxiliary Services, enabling 100+ VC firms to explore 50K+ labor policy data points via interactive dashboards. Built ETL pipelines with Airbyte, Fivetran, and Python to automate data ingestion from public APIs and PDF-extracted data sources, cutting manual reporting by 40%.

Data Science Intern

Jan 2023 – Jul 2023 · 6 mos · Nagpur, Maharashtra, India

- Designed an experimentation framework to evaluate campaign and pricing strategies using uplift modeling and causal inference techniques (e.g., inverse propensity scoring). Analyzed A/B test results across customer cohorts in SQL and Python, driving a 10% lift in campaign ROI and informing product-level pricing decisions.