Bruce N.

Key Skills

Software

Don't disclose

Top Subject Matter

SEO research and aged-domain evaluation using AI on web text

Compliance analytics and anomaly-based violation detection from member activity data

Legal Services & Contract Review

Top Data Types

Text

Document

Top Task Types

Text Generation

Freelancer Overview

Business Analyst in Contract Review, Compliance, and Legal Research. Brings 14+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Don't disclose. Education includes Bachelor of Arts, Wabash College (2016). AI-training focus includes data types such as Text and labeling workflows including Text Generation, Evaluation, and Rating.

Labeling Experience

M6 — Data Analyst (October 2025 - Present): built software systems by directing AI coding agents to run an aged-domain hunting and SEO recovery pipeline.

TextText Generation

Directed AI coding agents to build and operate an internal content/SEO pipeline that processes large-scale web text for ranking and recovery workflows. Implemented an on-server reader using local AI models to interpret and evaluate aged/expired domains sourced from Common Crawl. Used AI-supported scoring/tiering and recovery research to diagnose search-penalty causes and plan remediation. • Parsed and scored web content to tier aged domains for SEO value. • Ran AI-assisted page reading with local Ollama models. • Built automated nightly/background workflows to support the pipeline. • Developed recovery strategy based on analysis of real-world search behavior and patents.

2025 - Present

Herbalife — Data Analyst & MPC (Member Compliance) (February 2025 - October 2025): used data to detect rule-breaking by members via pattern/outlier analysis.

Don't discloseText

Used member-activity data analysis to detect rule-breaking patterns and outliers for Herbalife compliance. Translated behavioral signals into violation detection outcomes to support Member Compliance decision-making. Performed investigative analytics workflows that effectively label behaviors as likely violations based on detected anomalies. • Monitored member activity and identified outlier patterns. • Flagged potential rule violations for compliance review. • Performed data-driven detection using statistical/analytical methods. • Supported compliance monitoring and enforcement through analytics.

2025 - 2025

Education

Work History