Data Analyst

Overview

The Employee Experience Insights & AI Enablement Team seeks a Senior Insights Analyst to operate at the crossroads of AI strategy, IT operations, and enterprise analytics. This role is not a typical BI position but involves establishing the analytics framework that empowers the Central Technology team to comprehend, manage, and enhance AI investments while supporting operational intelligence throughout IT service delivery.

Key Responsibilities

• Develop executive-level dashboards tracking AI expenditures and their relation to strategic objectives, highlighting anomalies and efficiency indicators in a user-friendly format.
• Maintain and scale the AI cost analytics platform built on LiteLLM, Snowflake, and LangSmith into a robust observability system.
• Architect the integration of AI telemetry data with enterprise data platforms to enable detailed token usage attribution across teams and applications.
• Collaborate with Cloud Services, InfoSec, and Finance teams to ensure accurate, compliant AI spend governance aligned with enterprise reporting standards.
• Create and sustain dashboards and datasets that provide insights into IT service delivery performance globally across service desk, endpoint operations, and employee experience functions.
• Consolidate and normalize data from ServiceNow, DEX Performance Analytics, collaboration tools, and other operational sources into thorough, analysis-ready datasets.
• Analyze service delivery data to identify patterns, challenges, and improvement opportunities, delivering actionable insights to leadership.
• Respond promptly to diverse ad-hoc data requests from IT and business stakeholders.
• Identify AI enablement opportunities by analyzing operational data, prioritizing them based on ROI, complexity, and strategic relevance.
• Partner with program and technology leaders to measure and report the impact of AI deployments, feeding insights into future planning.
• Design and implement frameworks to measure productivity impacts of AI on knowledge workers, capturing KPIs beyond adoption like time savings and output quality.
• Develop the infrastructure for collecting and reporting productivity signals across various AI tools and employee groups.
• Produce recurring reports on productivity impact targeting senior and executive audiences to guide AI investment decisions.
• Architect scalable analytics platforms integrating Snowflake, Microsoft Fabric, LiteLLM, ServiceNow, and multiple data sources.
• Lead the transition from static reports to dynamic, interactive AI-enhanced dashboards employing Power BI, Fabric, and agentic tools.
• Establish data standards, integration methods, and governance protocols to support platform scalability with new AI tools and data additions.
• Assess and recommend analytics tools to maintain a state-of-the-art, enterprise-aligned analytics platform.

Qualifications

• Demonstrated experience in data analytics, reporting, and dashboard development with a portfolio including operational ITSM, AI reporting, and executive-facing strategic analyses.
• Proficiency in Snowflake or Microsoft Fabric for data pipeline creation, transformations, and analytic delivery.
• Expertise in Microsoft Power BI for developing dashboards and reports for stakeholders.
• Experience merging data from APIs, CSVs, event streams, and SaaS sources into analysis-ready formats.
• Strong analytical and communication capabilities to convert complex data into clear executive narratives.
• Complete ownership of the data solution lifecycle from requirements to deployment and iteration.
• Ability to work independently in fast-paced settings with shifting priorities and evolving needs.
• Collaborative approach with experience interacting across technical and non-technical teams.

Preferred Experience

• Familiarity with LiteLLM, LangSmith, or comparable LLM observability and expense monitoring platforms.
• Understanding of AI/LLM cost dynamics, token economics, model pricing, and usage attribution.
• History of building AI-assisted or agentic analytics solutions, potentially with tools like ClaudeCode.
• Knowledge of ServiceNow ITSM or HRSD data models.
• Background in workforce analytics, productivity measurement, or digital employee experience platforms.
• Exposure to enterprise AI platforms including Anthropic/Claude, OpenAI, Google Gemini, or AWS Bedrock.