About the job
CloudFactory is on a mission to use AI for global impact, combining technology with a diverse team to turn raw data into insights that matter. The company’s work aims to deliver real-world results by making sense of complex information.
CloudFactory is more than a workplace. The team values strong relationships and meaningful work, with a focus on learning, earning, and serving. The goal: connect one million people to impactful jobs and develop leaders who inspire others.
Our Culture
CloudFactory builds an environment where people feel empowered, valued, and encouraged to be themselves. Core values include:
- Mission-Driven: Focused on creating economic and social impact.
- People-Centric: Prioritizing growth, well-being, and inclusivity.
- Innovative: Embracing change and collaborative improvement.
- Globally Connected: Encouraging cooperation across cultures and viewpoints.
Role Overview: Senior Data Analyst
This Senior Data Analyst position sits in Kathmandu, Nepal. The role centers on delivering analytical insights for client projects and internal enterprise initiatives within Enterprise QSE. The analyst works closely with teams from Quality, Delivery, Workforce, Finance, Technology, and other departments. Responsibilities include applying statistical reasoning, hypothesis-driven analysis, and sound analytical practices to spot performance risks, explain operational issues, and support better decision-making. This position suits someone who enjoys moving beyond standard reporting, thrives in data-rich settings, and helps strengthen analytical standards across the company.
What You Will Do
Advanced Performance Analysis
- Analyze accuracy, throughput, SLA adherence, workforce trends, queue performance, and financial or service risk indicators in depth.
- Use structured analytical methods to distinguish between routine performance variation and significant deviations.
- Identify causes for quality shifts, adjustment spikes, instability patterns, and declines in workstreams.
- Segment data to reveal patterns tied to worker groups, task types, shifts, workflows, or use cases.
- Summarize findings and provide clear, actionable recommendations to Quality and Delivery leaders.
Statistical Analysis & Performance Risk Interpretation
- Apply statistical techniques to test hypotheses, compare performance segments, and assess observed metrics to guide strategic choices.

