AI Data Analyst

Glean Work is hiring an AI Data Analyst in Bengaluru, India. Level rates it ; you can apply on Level.

AI in this role

ai-agentsai-data-labelingnlp

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. You'll be 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.

How we rate this

AI Data Analyst at Glean Work rates 68 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.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ 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.

Key facts

AI Data Analyst is an open job at Glean Work.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Bangalore, India.
The job was posted on October 7, 2026.
Seniority: mid.
Applications are handled by Glean Work. Apply on Glean Work

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsAI Data LabelingNLP

Also common in data analyst jobs at this level

Python dbt Machine learning Spark Airflow

Pay

Typical data analyst job: $110k

This posting doesn't list pay. Use the typical data analyst figure when pay comes up. See data analyst jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
How do you keep labeling instructions consistent across a large annotation team?
What NLP problem have you worked on, and how did you measure whether it actually worked?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: AI agents, AI Data Labeling, and NLP. 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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