Senior IT Ops Analyst

YO AI Labs · AI Training Data & Annotation · AI Evaluation & Observability · Python · SQL · Tableau · Power BI · QlikSense · ETL/ELT · 7 days ago

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Location

In office (Bengaluru)

Seniority

Senior · 7+ years exp

Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 5, 2026.

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YO AI Labs

YO AI Labs is an artificial intelligence platform specializing in AI model training, evaluation, and data annotation services. Headquartered in San Francisco, California, United States, the company connects domain experts and remote specialists across the globe to review, test, and benchmark generative AI model outputs. Through its decentralized workforce solutions and structured evaluation workflows, it enables frontier technology developers to enhance the accuracy, safety, and reliability of next-generation artificial intelligence systems.

yoailabs.com · HQ: San Francisco, United States · AI Evaluation & Observability · AI Training Data & Annotation · 51-200 employees

Tech stack of YO AI Labs

Role : Sr. IT Ops Analyst / Data Analyst

Domain : Information technology (IT)

Job Type: Full Time

Location : India - Bangalore

Experience: 7 - 14 Years

Role Overview: This role leads data analytics, telemetry processing, and operational insights derived from digital workspace infrastructure and proprietary AIOps platforms. The position converts raw system performance metrics into actionable business intelligence, cost optimization strategies, and client-facing Experience Level Agreement (XLA) scorecards.

Key Responsibilities:

Telemetry & Operational Analytics: Analyze enterprise VDI/EUC performance metrics, active concurrency sessions, resource utilization, and application delivery data.
XLA Scorecarding: Build dynamic analytics dashboards highlighting End-User Experience scores, proactive issue resolution rates, and system stability trends.
Capacity Planning & Cost Optimization: Deliver predictive modeling for cloud resource consumption (Azure, AWS, GCP) to optimize cloud spending for global enterprise accounts.
Client & Leadership Reporting: Design automated executive reports, quarterly business review (QBR) packs, and operational performance dashboards.
Team & Data Pipeline Management: Oversee a team of data analysts and BI engineers, refining ETL pipelines and data modeling standards.

Key Technical & Functional Requirements:

Advanced SQL, Python/R for data analysis and predictive modeling.
BI & Visualization Tools: Power BI, Tableau, or QlikSense.
Telemetry & Monitoring concepts: Metric correlation, time-series data, AIOps telemetry, log analysis (Splunk / Elastic / Datadog).

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