AI Data Analyst
Bangalore, India
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Location: This role is hybrid (4 days a week in our offices). Compensation & Benefits:
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingGlean is seeking an AI Data Analyst to help power the human evaluation system behind Glean’s AI product quality.
Run ongoing human labeling for priority AI workflows, including response quality, task success, MCP and tool use, end-to-end Cowork-style workflows.
Run ongoing human labeling of AI responses, task success and tool use
Triage bad-query reports, downvotes and escalations; categorize failure modes
Analyze recurring patterns such as hallucinations and retrieval failures
Maintain labeled datasets, golden sets and regression slices
Validate LLM-as-a-judge outputs against human labels
From the employer’s posting
Glean is seeking an AI Data Analyst to help power the human evaluation system behind Glean’s AI product quality. This role sits at the centre of response quality, competitive benchmarking, and release readiness. You will evaluate AI outputs, label and categorize failure modes, maintain high-quality benchmark data, and help ensure the datasets and evals we rely on are realistic, consistent, and tied to measurable product quality lift. This is a highly cross-functional role. You will work closely with QA, Engineering, Product, and the evals team to convert ambiguous quality issues into structured data, actionable feedback, and repeatable quality signals.
Run ongoing human labeling for priority AI workflows, including response quality, task success, MCP and tool use, end-to-end Cowork-style workflows.
Run ongoing human labeling for priority AI workflows, including response quality, task success, MCP and tool use
Triage bad-query reports, downvotes, escalations, and routed quality issues; categorize failure modes
Perform qualitative analysis to identify recurring patterns such as hallucinations, retrieval failures, tool-use issues
Maintain high-quality labeled datasets, golden sets, and regression slices
validate LLM-as-a-judge outputs against human labels
What you’ll bring
All qualificationsCore experience
- 3–5 years of experience in data labeling, data analysis, QA, or a related field.
- Experience evaluating AI-generated outputs or working with NLP, search, recommendation, or other ML systems.
- Familiarity with structured qualitative analysis, basic SQL/data retrieval, and spreadsheet-based workflows.
- Ability to work independently in ambiguous, fast-moving environments and collaborate effectively across functions.
Qualification wording
3–5 years of experience in data labeling, data analysis, QA, or a related field.
Experience evaluating AI-generated outputs or working with NLP, search, recommendation, or other ML systems.
Familiarity with structured qualitative analysis, basic SQL/data retrieval, and spreadsheet-based workflows.
Ability to work independently in ambiguous, fast-moving environments and collaborate effectively across functions.
Tools in this posting
- SQL
Source — Tool mentions in context
- Experience evaluating AI-generated outputs or working with NLP, search, recommendation, or other ML systems. - Familiarity with structured qualitative analysis, basic SQL/data retrieval, and spreadsheet-based workflows. - Clear written and verbal communication skills, with the ability to explain findings to both technical and non-technical audiences.
About Glean
Glean is the Work AI platform that helps everyone work smarter with AI.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 13, 2026 · 16 days ago
- Recorded sightings
- 28
- Last seen by us
- Oct 30, 2026
- Reposted
- once since Aug 24, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Already applied? Track this application
Job description
- Run ongoing human labeling for priority AI workflows, including response quality, task success, MCP and tool use, end-to-end Cowork-style workflows.
- Triage bad-query reports, downvotes, escalations, and routed quality issues; categorize failure modes and feed clean analysis back to partner teams.
- Perform qualitative analysis to identify recurring patterns such as hallucinations, retrieval failures, tool-use issues, weak grounding, and poor workflow completion.
- Follow and improve labeling guidelines and rubrics so judgments are consistent, realistic, and useful for model and product improvement.
- Maintain high-quality labeled datasets, golden sets, and regression slices; monitor coverage, drift, leakage, and difficulty distribution.
- Participate in calibration exercises with human graders and validate LLM-as-a-judge outputs against human labels to improve consistency and judge quality.
- Partner with engineers, PMs, QA, and eval owners on pre/post-change quality reads, benchmark updates, and release-readiness decisions.
- Contribute to recurring quality reporting by surfacing top failure modes, coverage gaps, quality shifts, and actionable recommendations.
- 3–5 years of experience in data labeling, data analysis, QA, or a related field.
- Strong analytical judgment and attention to detail, with the ability to apply nuanced rubrics consistently.
- Experience evaluating AI-generated outputs or working with NLP, search, recommendation, or other ML systems.
- Familiarity with structured qualitative analysis, basic SQL/data retrieval, and spreadsheet-based workflows.
- Clear written and verbal communication skills, with the ability to explain findings to both technical and non-technical audiences.
- Ability to work independently in ambiguous, fast-moving environments and collaborate effectively across functions.
By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement, and I agree to the terms.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bangalore, India
Location: This role is hybrid (4 days a week in our offices). Compensation & Benefits:
More source context
We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. #LI-HYBRID AI-First Mindset at Glean:
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.