Data Analyst - Taxonomy and Classification - 1030

Lightcast•Moscow, ID

About The Position

The Data Analyst – Taxonomies and Classification at Lightcast is responsible for evaluating and improving the quality, coverage, and relevance of Lightcast’s enriched data, models, and taxonomies. This role focuses on analyzing and classifying large-scale labor market data, resolving data ambiguities, developing decision-making frameworks, and ensuring data quality standards. The ideal candidate is analytical, detail-oriented, and passionate about identifying patterns in data to improve taxonomy structures and data products.

Requirements

Bachelor’s degree in Data Analytics, Information Systems, Computer Science, Mathematics, or a related technical field; advanced degree or equivalent practical experience preferred.
1–3 years of experience working with ML classification models, taxonomy development, or maintaining proprietary/government taxonomies across various data types.
Experience with SQL and data extraction/query languages such as Elasticsearch, KQL, or SPARQL.
Understanding of text analysis, natural language processing (NLP), machine learning (ML), and statistical analysis techniques preferred.
Experience with AI coding copilots such as Claude or Codex is a plus.

Responsibilities

Interpret and classify natural language data such as job titles, job postings, and company names using NLP-related methodologies.
Perform root cause analysis to identify and resolve data quality and classification issues.
Develop and maintain decision-making criteria, enrichment processes, and quality assurance standards.
Conduct research to support taxonomy improvements and identify new use case opportunities.
Execute data extraction, ETL, and data mining processes using SQL, Python, R, Excel, or similar tools.
Work with relational databases such as Snowflake, Postgres, SQL Server, or SQLite.
Communicate complex data findings and taxonomy-related issues to technical teams and stakeholders.
Respond to customer feedback and questions related to datasets and taxonomy accuracy.
Contribute to product roadmapping, project scoping, and process improvements.
Utilize visualization and project management tools such as Kibana, Looker, Tableau, Jira, Wrike, or Asana as needed.