QA Engineering 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 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.

Responsibilities
Data Analysis
● Quality Audits
○ Perform quality audits on annotated datasets to ensure that they meet
established guidelines and quality benchmarks.

● Statistical Reporting
○ Leverage statistical based quality metrics such as F1 score and
inter-annotator agreement to evaluate data quality.

● Root Cause Analysis
○ Analyse annotation errors, trends, project processes, and project
documentation to identify and understand the root cause of errors and
propose remediation strategies.

● Edge-Case Management
○ Resolve and analyse edge-case annotations to ensure quality and identify
areas for improvement.

● Tooling
○ Become proficient in using annotation and quality control tools to perform
reviews and track quality metrics.

● Guidelines
○ Become an expert in the project specific guidelines and provide feedback for
potential clarifications or improvements.

Continuous Improvement
● Automation
○ Identify opportunities to use automation to help enhance analytics, provide
deeper insights, and improve efficiency.

● Documentation
○ Develop and maintain up-to-date documentation on quality standards,
annotation guidelines, and quality control procedures.

● Feedback
○ Provide regular feedback that identifies areas for improvement across the
annotation pipeline.
Collaboration & Communication
● Cross-Functional Teamwork
○ Work closely with key project stakeholders and clients to understand project
requirements and improve annotation pipelines.

● Training

○ Assist with training annotators, providing guidance, feedback, and support to
ensure data quality.

● Reporting
○ Provide regular updates that highlight data quality metrics, key findings, and
actionable insights for continuous process improvements.

Required Qualifications
● Bachelor's degree in a technical field (e.g. Computer Science, Data Science) or
equivalent practical experience.
● 1+ years of experience as a data analyst with exposure to data quality and/or data
annotation - ideally within an AI/ML context.
● Familiarity with the basic concepts of AI/ML pipelines and data.
● Strong analytical and problem-solving skills with an exceptional eye for detail.
● Excellent written and verbal communication skills, with the ability to clearly articulate
quality issues and collaborate with diverse teams.
● Ability to work independently and manage time effectively to meet deadlines.
● A strong problem-solver who thinks critically and drives innovation and continuous
optimisation.
● A quick learner with the ability to work independently in a fast-paced environment.
● A strong focus on detail, balanced against strategic priorities.
● A positive can-do attitude and the ability to easily adapt to new environments.
● Not afraid to speak up.

Preferred Qualifications
● Familiarity with data annotation tools (e.g. Labelbox, Dataloop, LabelStudio etc.).
● Experience working with multi-modal AI/ML datasets (images, videos, text, audio).
● Prior experience in an agile or fast-paced tech environment with exposure to AI/ML
pipelines.
● Knowledge of programming languages (e.g. Python).
● Knowledge of the concepts and principles of data quality for AI/ML models and the
impacts it can have on model performance.
● Working understanding of common quality metrics and statistical methods used in
AI/ML data quality.
● Knowledge of AI/ML concepts and experience with data for AI/ML models.
● Experience in prompt engineering and leveraging LLMs in your day-to-day work.

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