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Shiviam357/README.md

Principal Recruiter & HR Analyst...Currently leveraging my background in Electronics & Communications Engineering to transition into Data Analytics and Data Science. Since 2022, integrating Generative AI to improve productivity by 30%

Engineering Foundation: B.Tech in Electronics & Communications Engineering.

Technical Toolkit:

AI: Advanced Prompt Engineering (ChatGPT, Gemini). Programming: Python (Data Cleaning, Automation, Web Scraping). Data: Intermediate Excel (Pivot Tables, Data Visualization).

HR Document Automation: Candidate Packet Generator

Business Context: In high-volume US Staffing and recruitment, managing submission packets is a manual, time-intensive task. Recruiters often have to manually combine resumes, Right to Represent (RTR) forms, and ID proofs into a single PDF for client submission.

The Problem:

Manual Effort: Manually merging documents for dozens of candidates daily leads to "administrative fatigue."

Data Integrity: Manual handling increases the risk of attaching the wrong document to a candidate's profile.

Turnaround Time: High volume recruitment requires speed to maintain pipeline health.

The Solution: Developed a Python-based automation tool that programmatically merges various candidate document types into organized, professional PDF packets. This ensures 100% data integrity for submission packets while significantly reducing administrative overhead.

Technical Features:

Automated Merging: Uses Algorithmic Automation to batch-process multiple PDF and document files. Workflow Integration: Designed to streamline high-volume submission workflows common in VMS/MSP environments. Error Handling: Ensures that only complete packets are generated, maintaining strict compliance with US Work Visa and tax term documentation requirements.

Impact & Results:

Efficiency: Reduced administrative turnaround time by approximately 30%. Accuracy: Achieved 100% Data Validation in candidate submission packets. Scalability: Enabled the team to support high-volume requirements across Aerospace, Banking, and Retail sectors more effectively. Future Scope: Integrating OCR (Optical Character Recognition) to automatically extract candidate details from the merged PDFs for automated ATS entry.

Tech Stack:

Language: Python Libraries: PyPDF2 / OS / Sys (for file manipulation and system pathing) Domain Knowledge: US Staffing Compliance (H1B, GC-EAD, W2, C2C)

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  1. People-Analytics-Portfolio People-Analytics-Portfolio Public

    Data-driven insights for HR strategy, focusing on recruitment metrics, talent pipeline health, and employee lifecycle analysis.

    Python 1

  2. Shiviam357 Shiviam357 Public

    8+ years HR Professional transitioning into Data Science | Specializing in Python Automation, Generative AI, and People Analytics.

    1

  3. Generative-AI-Applications Generative-AI-Applications Public

    Leveraging LLMs and Prompt Engineering to optimize candidate persona building and automate content generation in recruitment.