David T.

Key Skills

Software

No software listed

Top Subject Matter

Operational/financial and identity dataset validation

Languages - fluent in Russian and Armenian as well

Top Data Types

Text

Document

Top Task Types

Data Collection

Freelancer Overview

IT Business Analyst in Contract Review, Compliance, and Legal Research. Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Python, SQL, and Tableau. Education includes Bachelor of Science, University of California, Irvine (2024). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Data Collection.

Labeling Experience

IT Business Analyst (May 2025 - May 2026) — automated data validation, discrepancy tracking, and workflow reporting support

Data Collection

In this role, the candidate built automated data validation and workflow automation using Python and SQL to ensure data quality for downstream business processes. While this was not manual human annotation, it functioned as structured labeling/verification of dataset correctness (e.g., identifying discrepancies and validating records) to make the data trustworthy for reporting and decisioning. The work included validating large financial and identity datasets to confirm records conformed to expected formats and rules. • Automated data pipelines and reporting systems to validate operational data • Conducted large-scale data validation across 100,000+ records to reduce errors • Developed reusable SQL queries and structured datasets for consistent analysis • Collaborated with technical teams to resolve data integrity issues

2025 - 2026

Data Analyst (Contract) (May 2024 - May 2025) — automated validation workflows and dashboarding

Data Collection

The candidate created automated data validation and analysis workflows using Python and SQL to improve accuracy and consistency of financial datasets used for reporting. They also used Tableau dashboards to monitor key performance metrics derived from those validated datasets. The activities emphasized preparing clean, reliable data for analytics rather than manual labeling. • Implemented automated validation workflows for financial data consistency • Built Tableau dashboards for KPI monitoring and decision support • Performed cost and operational analysis to recommend changes based on data • Improved data pipeline structure and reporting processes with engineering teams

2024 - 2025

Education

Work History