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AI Data Analyst

Glean

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This role on the market

7,296 open data roles across 659 companies are on ApplySarthi right now, most of them in Bengaluru (415), Hyderabad (313), Mumbai (155).

What data roles keep asking for: AWS (24%), SQL (23%), Python (22%) — counted across their open postings here.

LLMs jobs · NLP jobs · SQL jobs · SaaS jobs

Glean has 130 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

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Questions you are likely to be asked

  1. Why do you want to join Glean?
  2. What is your experience with LLMs? Tell me one thing you learned the hard way.
  3. Walk me through a model you built, from the data to how it was used.
  4. How did you know your model was actually good, and not just good on your test set?
  5. Tell me about a time the data was messy or wrong. What did you do?

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About Glean:
 
Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.
 
At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.
 
Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.
 
If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.
 
About the Role:
 
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.
 
You will: 
  • 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.
About you:
  • 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.
Location:
 
This role is hybrid (4 days a week in our offices).
 
Compensation & Benefits:
 
Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
 
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:
 
At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required.
 
Global Data Privacy Notice for Job Candidates and Applicants:
 
Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy. By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement.

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.  

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Listed on greenhouse · posted 2026-08-24. ApplySarthi collects openings and links to application pages; the role is advertised by Glean, not by us.