Data Quality Manager | Anonas

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 the fastest-growing 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.

It started with one ridiculously good idea to create a different breed of Business Processing Outsourcing (BPO)! We at TaskUs understand that achieving growth for our partners requires a culture of constant motion, exploring new technologies, being ready to handle any challenge at a moment’s notice, and mastering consistency in an ever-changing world.

What We Offer: At TaskUs, we prioritize our employees' well-being by offering competitive industry salaries and comprehensive benefits packages. Our commitment to a People First culture is reflected in the various departments we have established, including Total Rewards, Wellness, HR, and Diversity. We take pride in our inclusive environment and positive impact on the community. Moreover, we actively encourage internal mobility and professional growth at all stages of an employee's career within TaskUs. Join our team today and experience firsthand our dedication to supporting People First.

What does a Data Quality Manager really do? Think of yourself as the champion of high-quality data—leading the charge in setting the standard for excellence across our AI data projects. You’ll build and optimize quality frameworks, lead a team of quality analysts, and use data-driven strategies to improve performance, reduce errors, and ensure exceptional output across multiple projects.

You’ll work cross-functionally with operations, engineering, and client services teams to ensure that our AI data annotation and validation work exceeds expectations—every time.

As a Quality Manager, you will:

Strategic Quality Leadership

• Design, document, and refine quality assurance processes and SOPs that drive consistent, accurate, and high-quality outputs.
• Establish quality metrics (e.g., F1 score, inter-annotator agreement) that align with client goals and industry benchmarks.
• Proactively review workflows to reduce errors, identify gaps, and boost efficiency across annotation pipelines.
• Act as a subject matter expert on quality—training teams, reviewing outputs, and implementing continuous improvements.

Data Analysis & Reporting

• Lead deep-dive data analyses to uncover trends, identify root causes of quality issues, and improve annotation workflows.
• Build and manage dashboards that provide real-time visibility into quality metrics and project health.
• Translate insights into actionable reports for internal teams and clients—highlighting wins, risks, and opportunities for improvement.
• Partner with stakeholders across operations, engineering, and client services to align quality goals and ensure project success.

Team & Tool Management

• Lead and mentor a high-performing team of Data Quality Analysts. Foster a culture of excellence, accountability, and continuous learning.
• Oversee the setup, configuration, and optimization of annotation and QA tools (e.g., Labelbox, Dataloop, LabelStudio).
• Explore, evaluate, and implement new technologies and automation tools to streamline quality assurance and enhance performance.

Do you have what it takes to become a Quality Manager?

Requirements:

• Bachelor’s degree in Computer Science, Data Science, or a related technical field—or equivalent experience.
• 3+ years of experience in data quality, data operations, or QA—ideally in AI/ML or data annotation environments.
• Strong understanding of annotation workflows and statistical quality metrics like F1 score and inter-annotator agreement.
• Proven experience in leading teams and managing large-scale, high-volume quality operations.
• Hands-on experience with QA and annotation platforms (e.g., Labelbox, Dataloop, LabelStudio).
• Advanced data analysis skills using Excel, Google Sheets, and SQL; familiarity with Python is a plus.
• Exceptional communication skills with the ability to present data insights to technical and non-technical audiences.
• Strong organizational skills with a proactive, solutions-focused mindset.

Nice to have:

• Experience working in fast-paced tech or agile environments, particularly with AI/ML pipelines.
• Background in managed services, vendor-driven operations, or BPO setups.
• Familiarity with prompt engineering or LLM-assisted workflows to enhance annotation and validation.
• Awareness of ethical AI practices and compliance standards.

How We Partner To Protect You: TaskUs will neither solicit money from you during your application process nor require any form of payment in order to proceed with your application. Kindly ensure that you are always in communication with only authorized recruiters of TaskUs.

DEI: In TaskUs we believe that innovation and higher performance are brought by people from all walks of life. We welcome applicants of different backgrounds, demographics, and circumstances. Inclusive and equitable practices are our responsibility as a business. TaskUs is committed to providing equal access to opportunities. If you need reasonable accommodations in any part of the hiring process, please let us know.

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