Sanay S.

Key Skills

Software

No software listed

Top Subject Matter

Legal Services & Contract Review

Regulatory Compliance & Risk Analysis

Legal Research & Document Analysis

Top Data Types

Video

Text

Document

Top Task Types

Segmentation

Freelancer Overview

During my Data Integrity internship at Ubiquity, I worked directly with large-scale data quality and labeling-adjacent tasks, developing Python algorithms and SQL queries to de-duplicate and clean records for over 150,000 customers. This involved precise record matching, identifying repeat entries by address and metadata, and applying consistent labeling logic at scale — work that reduced downstream BI dashboard errors by 20% and improved customer segmentation accuracy by over 40%. Earlier, as an Internal Audit intern, I reconciled financial records with 100% accuracy across $100,000+ in monthly cash flow, reinforcing the meticulous attention to detail and consistency that high-quality data annotation demands. Beyond professional experience, I've built data-centric projects that strengthen my fit for AI training work, including a Python stock analysis tool that processed five years of historical data across 50+ companies and a financial dashboard analyzing multi-year datasets. I'm proficient in Python, SQL, and Excel, comfortable working within structured guidelines and quality-control standards, and bring strong analytical judgment from finance and accounting coursework (4.00 technical GPA). Combined with my ability to follow detailed protocols, maintain accuracy at scale, and collaborate cross-functionally, I'm well-positioned to deliver reliable, consistent labeling and contribute to building high-quality training datasets.

Labeling Experience

Data Integrity Intern

VideoSegmentation

As a Data Integrity Intern, they developed Python and SQL solutions to clean and reconcile customer data for a fiber internet service. They identified duplicates by matching records using addresses and customer metadata. They collaborated with engineering and product teams to implement data hygiene protocols that improved reporting quality and segmentation accuracy. • Developed Python-based data cleaning algorithms and SQL queries to de-duplicate over 150,000 customer records • Matched repeat entries using address and customer metadata to ensure accurate records • Implemented data hygiene protocols in collaboration with cross-functional engineering and product teams • Reduced downstream BI dashboard errors by 20% and improved customer segmentation accuracy by over 40%

2025 - 2025

Education

Work History