Associate Data Taxonomist - 1056
AI Summary
The Associate Data Taxonomist at Lightcast develops and maintains standardized taxonomies for labor market data to ensure consistency, quality, and accuracy across the organization.
About this role
The Associate Data Taxonomist at Lightcast develops and maintains standardized taxonomies for labor market data to ensure consistency, quality, and accuracy across the organization. This role analyzes labor market data, creates standardized classifications, collaborates with cross-functional teams, and supports data governance initiatives that enhance labor market intelligence.
Major Responsibilities:
Develop and maintain taxonomies for labor market data, including job titles, skills, education requirements, and industry classifications.
Analyze labor market data to identify patterns and establish standardized terms and classifications.
Partner with cross-functional teams to ensure taxonomies align with business needs and are integrated into data models and databases.
Implement and maintain data governance processes to ensure data quality, consistency, and accuracy.
Support labor market data integration and migration projects while maintaining taxonomy integrity.
Organize and analyze large, unstructured datasets.
Monitor industry trends and best practices related to labor market taxonomies, ontologies, and data governance.
Education and Experience:
Bachelor's degree in Computer Science, Information Science, Library Science, or a related field.
1+ years of experience in labor market data management, analytics, taxonomy development, or a related field.
Strong analytical and problem-solving skills with exceptional attention to detail.
Experience working with large, unstructured datasets.
Familiarity with data modeling and database design principles.
Experience with SQL, Elasticsearch, KQL, SPARQL, or similar data query languages is preferred.
Experience with Python or R and data visualization tools such as Tableau, Looker, or Kibana is a plus.
Knowledge of labor market taxonomies and ontologies (e.g., NAICS, CIP, ESCO, O*NET-SOC) is preferred.
Familiarity with NLP or machine learning concepts is a plus.
Excellent written and verbal communication skills and the ability to work independently and collaboratively.
