Data Quality Analyst

8 hours ago

General Santos, Soccsksargen, Philippines beBeeDataQuality Full time $50,000 - $100,000

About TaskUs

TaskUs is a provider of outsourced digital services and next-generation customer experience to fast-growing technology companies.

The company serves clients in sectors including social media, e-commerce, gaming, streaming media, food delivery, ride-sharing, HiTech, FinTech, and HealthTech.

The People First culture has enabled the company to expand its workforce to approximately 45,000 employees globally.

We have a presence in twenty-three locations across twelve countries.

Ai Data Quality Specialist

Role Overview

This role requires a diligent, detail-focused professional who can maintain annotation standards and drive continuous improvements to keep AI data accurate, efficient, and scalable.

Key Responsibilities

  • Perform quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks.
  • Leverage metrics such as F1 score and inter-annotator agreement to evaluate data quality.
  • Analyze annotation errors, trends, and project documentation to identify root causes and propose remediation strategies.
  • Resolve and analyze edge-case annotations to ensure quality and identify improvement areas.
  • Proficiently use annotation and quality control tools to perform reviews and track quality metrics.
  • Become an expert in project guidelines and provide feedback for clarifications or improvements.
  • Identify automation opportunities and contribute to documentation of quality standards and procedures.

Requirements

  • 1+ years of experience as a data analyst with exposure to data quality and/or data annotation, ideally in an AI/ML context.
  • Familiarity with basic concepts of AI/ML pipelines and data.

Benefits

  • Competitive salaries and comprehensive benefits.
  • Inclusive environment and support for internal mobility and professional growth.

Impact Statement

  • Guard data integrity through audits: Conduct quality audits against guidelines and benchmarks to uphold data reliability.
  • Pinpoint and resolve annotation issues: Analyze error patterns and root causes to elevate quality.
  • Optimise annotation processes: Proficiently use QA tools, propose automation, and maintain documentation of standards.
  • Collaborate and coach: Work with stakeholders and annotators to clarify requirements and support skill development.
  • Track and communicate quality performance: Regularly report metrics and insights to drive continuous improvements.

You will be working remotely and enjoying flexible work arrangements. Every dataset is unique, and your contributions will have a visible impact on AI model performance. Room to grow and opportunities for professional development are available within this team.

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