Taxonomy Analyst

 Posted a day ago
  
 Brazil
  
⭐ 5-10 years experience
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AI Summary

The role involves labeling, annotating, and classifying complex job and resume data to optimize data classification models. The analyst will standardize job titles and perform data cleanup and localization for global markets.

Position: Senior Taxonomy Analyst (English & Spanish Roles Available)

Location: Remote from LATAM

Contract Type: Full-time (Vendor)

Time Zone Alignment: CT

About In All Media

We are a Managed Nearshore Teams provider headquartered in Austin, specializing in building and embedding high-performing software development teams. From design to deployment, we deliver customized solutions by connecting global talent with innovative client projects. Our model allows you to work on international challenges, collaborate with diverse teams, and grow your career while being part of a company that values expertise, creativity, and impact.

Project Overview

The project focuses on scaling and refining data taxonomy operations for international employment data. The main objective is to optimize data classification models to ensure job listings and resumes are accurately cataloged, cleaned, and localized. We are currently hiring for two separate tracks for this project: one dedicated to English language operations and another dedicated to Spanish language operations. As a Senior Taxonomy Analyst, you will bridge the gap between raw, unstructured career data and highly optimized, localized market assets to drive global data accuracy.

Key Responsibilities

  • Taxonomy Operations: Support daily taxonomy operations by labeling, annotating, and classifying complex job and resume data.
  • Data Standardization: Standardize job titles and accurately map occupations across core global datasets.
  • Quality Assurance: Review and validate metadata to optimize overall taxonomy quality, ensuring all outputs remain accurate and highly consistent.
  • Cleanup & Localization: Perform data cleanup and localization workflows specifically tailored for global markets while strictly adhering to data labeling guidelines.
  • Data Evaluation: Process and evaluate high-volume datasets using strong pattern recognition skills and sharp attention to detail.

Must-Have Skills

  • Language Fluency: Native-level fluency in English (for the English-operating role) OR native-level fluency in Spanish (for the Spanish-operating role).
  • Taxonomy Experience: Prior proven experience in data taxonomy, metadata management, or content classification.
  • Data Labeling & Validation: Strong hands-on experience in data labeling/annotation, data validation, and reviewing high-volume datasets.
  • Analytical Rigor: Exceptional analytical skills, sharp attention to detail, strong pattern recognition, and the ability to exercise sound judgment under specific framework guidelines.
  • Localization Expertise: Direct experience working with localization workflows or multilingual content systems.

Nice-to-Have Skills

  • Domain Expertise: Direct knowledge of HR (Human Resources) systems, talent acquisition, or job taxonomy structures.
  • Data Tools: Basic familiarity with SQL (Structured Query Language), advanced Excel, or Google Sheets for data manipulation.
  • AI & LLM Tools: Hands-on exposure to Large Language Models (LLMs) and generative AI tools such as ChatGPT, Gemini, or Claude for data augmentation or classification.
  • Geographic Market Knowledge: Specific market knowledge of global English regions such as Ireland, India, the United Arab Emirates (UAE), Australia, or Singapore is highly preferred.

Time Zone & Collaboration

This role is 100% remote from LATAM and requires consistent alignment and overlap with teams operating within the Central Time (CT) zone. Flexibility is expected to accommodate key ceremonies, stand-ups, and collaborative sessions within standard Austin business hours.

Language

All internal workflows, documentation, and specific operational deliverables will be conducted primarily in the language of the chosen track (English or Spanish).

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