AI Data Quality Analyst

About TaskUs

TaskUs is a provider of outsourced digital services and next-generation customer experience to fast-growing technology companies, helping its clients represent, protect and grow their brands. Leveraging a cloud-based infrastructure, TaskUs serves clients in sectors including social media, e-commerce, gaming, streaming media, food delivery, ride-sharing, HiTech, FinTech, and HealthTech.

The People First culture at TaskUs has enabled the company to expand its workforce to approximately 45,000 employees globally. Presently, we have a presence in twenty-three locations across twelve countries, which include the Philippines, India, and the United States.

We started with a goal to create a different breed of Business Processing Outsourcing (BPO). TaskUs focuses on growth for partners through a culture of motion, readiness to handle challenges, and consistency in a changing world.

What We Offer

At TaskUs, we prioritize our employees\' well-being with competitive salaries and comprehensive benefits. Our People First culture is reflected in departments such as Total Rewards, Wellness, HR, and Diversity. We foster an inclusive environment and support internal mobility and professional growth. Join TaskUs to experience our dedication to People First.

Why this role exists : As AI-driven solutions expand across industries, ensuring the fidelity of training and evaluation datasets is essential for building reliable models. TaskUs needs a diligent, detail-focused Data Quality Analyst who can maintain annotation standards and drive continuous improvements to keep AI data accurate, efficient, and scalable.

Responsibilities

• Quality Audits – Perform quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks.

• Statistical Reporting – Leverage metrics such as F1 score and inter-annotator agreement to evaluate data quality.

• Root Cause Analysis – Analyze annotation errors, trends, and project documentation to identify root causes and propose remediation strategies.

• Edge-Case Management – Resolve and analyze edge-case annotations to ensure quality and identify improvement areas.

• Tooling – Proficiently use annotation and quality control tools to perform reviews and track quality metrics.

• Guidelines – Become an expert in project guidelines and provide feedback for clarifications or improvements.

• Continuous Improvement – Identify automation opportunities and contribute to documentation of quality standards and procedures.

What you’ll bring

Experiences you’ll bring

• 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.

Core skills you\'ll need

• Strong analytical and problem-solving skills with an exceptional eye for detail.

• Excellent written and verbal communication skills to clearly articulate quality issues and collaborate with diverse teams.

• Ability to work independently and manage time effectively to meet deadlines.

• Strong problem-solving, critical thinking, and continuous optimization mindset.

• Ability to work independently in a fast-paced environment with a focus on detail and strategic priorities.

• Positive can-do attitude and adaptability to new environments.

• Not afraid to speak up.

Nice to have

• Familiarity with data annotation tools (e.g., Labelbox, Dataloop, LabelStudio).

• Experience with multi-modal AI/ML datasets (images, videos, text, audio).

• Experience in agile or fast-paced tech environments with exposure to AI/ML pipelines.

• Knowledge of programming languages (e.g., Python).

• Understanding of data quality concepts for AI/ML models and their impact on model performance.

• Knowledge of quality metrics and statistical methods used in AI/ML data quality.

• Experience with data for AI/ML models and prompt engineering or leveraging LLMs.

Why you’ll love this role

• Work remote: Work from anywhere you’re most productive.

• Every dataset is unique: Audit, analyze, and improve AI/ML datasets across varied projects.

• Visible impact: Your quality checks and automation ideas will influence AI model performance.

• Room to grow: Build expertise in AI data quality and expand your influence as projects grow.

• Mission-driven team: Collaborate with analysts, engineers, and stakeholders to create accurate, reliable AI.

The impact you’ll make

• Guard data integrity through audits: Conduct quality audits against guidelines and benchmarks to uphold data reliability.

• Pinpoint and resolve annotation issues: Analyse 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.

How We Partner To Protect You : TaskUs will neither solicit money from you during the application process nor require payment to proceed. Please communicate only with authorized TaskUs recruiters.

DEI : TaskUs believes in innovation and performance through diverse people. We welcome applicants from all backgrounds and provide equal access to opportunities. If you need accommodations during the hiring process, please let us know.

We invite you to explore all TaskUs career opportunities and apply through the provided URL: continued at taskus.com/careers/