Level

Workday

AI Data Quality Analyst

Workday is hiring an AI Data Quality Analyst in Tel Aviv, Israel. Level rates it ; you can apply on Level.

AI in this role

Evaluate and annotate LLM-generated conversations and data to help improve artificial intelligence model performance.

claudecursorclaude-code
ai-evaluationai-data-labelingdata-annotationllm-evaluationdata-qualitynatural-language-processingai-testing

Your work days are brighter here.

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

About the Team

Are you an analytical person who is deeply interested in AI and LLM technology?
Is your superpower accurately categorizing information and identifying patterns?
Do you love to solve interesting challenges and make a direct impact through your work?
Join our Tel Aviv team as an AI Data Quality Analyst and help shape the future of AI. We're looking for analytical minds to contribute to our cutting-edge Large Language Model (LLM) project. In this unique role, you'll be performing LLM data quality tasks, ensuring consistency and quality in our conversations and helping design and support our flagship products.
This is more than a traditional data-labeling role. You will combine hands-on evaluation work with analytical thinking to help shape how our AI experiences evolve.
Sound like your perfect fit? We want to hear from you!

About the Role

As an AI Data Quality Analyst, you will evaluate LLM-generated conversations and other text-based data, identify trends and regressions, and partner with AI Engineers and Product Managers to improve model performance. In this role, you will:

  • Review and evaluate LLM-generated conversations and other text-based outputs against task-specific quality criteria and success metrics.
  • Perform high-quality annotation and data labeling to create reliable datasets for model training, benchmarking, and evaluation.
  • Monitor real production data to identify quality trends, regressions, and areas for improvement.
  • Identify qualitative patterns, recurring failure modes, regressions, and opportunities to improve model behavior and user experience.
  • Analyze evaluation results and clearly communicate insights, risks, and recommendations to cross-functional stakeholders.
  • Work closely with our AI Engineers and Product Managers to understand the data needs and ensure data quality processes align with goals, ensuring Paradox and Workday products remain top in class.

Why you should work at Workday and Paradox: 

  • Work side by side with passionate, purposeful people - Talent is our DNA and we pride ourselves on having the best!
  • Ability to make a big impact on a growing organization and drive your own growth
  • The opportunity to build the next big thing in Talent Acquisition technology
  • Internal and external professional development, coaching, and continuous education opportunities

About You


Required Qualifications:

  • Strong qualitative research and analytical skills, with the ability to detect meaningful patterns in large volumes of textual data.
  • Strong attention to detail, sound judgment, and a high bar for consistency and quality.
  • Creative, out-of-the-box thinking and a proactive approach to investigating ambiguous or unexpected model behavior.
  • Technical curiosity and confidence working across web-based tools, labeling platforms, dashboards, and evolving internal interfaces.
  • Strong English fluency, both written and verbal communication
  • A research-oriented background, such as Linguistics, Human-Computer Interaction, Cognitive Science, Psychology, or a related field.
  • Ability to work from our Tel Aviv, Israel office location.
  • Authorization to work in Israel.

Nice to Have:

  • 1+ years of experience with data labeling or annotation, ideally involving textual data, conversational data, or generative AI.
  • Experience working directly with LLM analysis, model evaluation, conversation quality assessment, or related AI quality workflows.
  • Experience using AI tools such as Claude Code, Cursor, or similar tools.

Our Approach to Flexible Work
 

With Hybrid Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so we require employees to work three days a week in the office and two days at home. This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together.


Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.


Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.


If you require a reasonable accommodation, you may email accommodations@workday.com, as far in advance as possible.


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How we rate this

AI Data Quality Analyst at Workday rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI EvaluationAI Data LabelingData AnnotationLLM EvaluationData QualityNatural Language ProcessingAI TestingClaude

Questions you could be asked

  1. How do you decide that one model's output is better than another's for a given task?
  2. How do you keep labeling instructions consistent across a large annotation team?
  3. Tell me about a project where data annotation was part of your work. What did you do?
  4. Tell me about a project where llm evaluation was part of your work. What did you do?
  5. Tell me about a project where data quality was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Evaluation, AI Data Labeling, Data Annotation, LLM Evaluation, and Data Quality. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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