Validate and maintain high-quality datasets for AI/ML workflows
Apply company data governance and compliance policies in daily work
Document data sources, definitions, and lineage for AI projects
Support metadata tagging and classification for AI datasets
Partner with data scientists to ensure accurate and consistent input data for models
Assist with feature preparation and data readiness for AI projects
Troubleshoot data issues with engineering and analytics teams
Provide guidance on best practices for data handling in AI pipelines
Collaborating across global teams in an agile environment
Review Neuron7(N7) dashboard to understand the nexus between data quality, N7 output, and end user expectations
Take actions to continually improve the data quality, work with N7 to improve the output to meet the end user expectations
Monitor and correct data drift to maintain the performance of the system
Any other function deemed necessary to perform

Requirements

English speaking (professional fluency)
Strong analytical background: experience working with datasets, dashboards, or data QA
Ability to work independently and drive projects with minimal guidance
Familiarity with SQL concepts, data management, or metadata practices (formal certification not required)
Exposure to AWS and/or Salesforce environments is a plus

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data validationdata governancedata compliancemetadata taggingdata preparationdata readinessdata troubleshootingdata qualitySQLdata management

Soft Skills

analytical skillsindependent workproject managementcollaborationcommunication