Staff IT Business Operations Data and AI Analyst

Qualcomm•San Diego, CA

11d•Onsite

About The Position

The Staff IT Business Operations Data and AI Analyst supporting the Office of the CIO is a senior individual contributor responsible for designing, building, and owning IT Business Operations analytics platforms that enable data and AI driven IT business operations insights and Office of the CIO decision making. This role owns complex analytical deliverables that transform the way we manage the business of IT through data and AI enabled solutions that drive IT decisions, deliver operational insights, and streamline processes across IT business operations. This role partners closely with IT, Finance, HR, Procurement and IT BOL stakeholders, and drives continuous improvement across areas such as IT budget management, resource rationalization and tracking, and cost transparency and reporting. Success in this role is defined by building scalable, data and AI‑enabled analytics and tools that advance IT Business Operations toward more standardized, proactive, and insight‑driven decision‑making and planning. This position is not eligible for Qualcomm immigration sponsorship. Position requires to be onsite in San Diego, 5 days a week.

Requirements

Bachelor’s degree in Information Systems, Data Analytics, Computer Science, Data Science, Machine Learning, Business Analytics, Mathematics or related field and 4-6 years of experience in data analysis, business intelligence, financial analytics, or IT business operations.
OR 8+ years of experience in data analysis, business intelligence, financial analytics, or IT business operations without a Bachelor’s degree.
Advanced experience with business intelligence and analytics platforms, including Power BI (required), Tableau, Databricks, and other modern data platform solutions like Acceldata, Fivetran, etc., with emphasis on data modeling, transformations, and performance optimization.
Advanced Excel skills, including complex formulas, pivot tables, Power Query, and financial models.
Strong experience designing and managing analytical data models for operational and/or financial use cases, including semantic models for BI tools (e.g., Power BI, Tableau, Excel data models).
Experience working with enterprise operational and financial data, such as general ledger, HR/headcount, procurement, contracts, asset, and IT service management data.
Experience applying AI to support data analysis, modeling, forecasting, trend identification, or insight generation within business or IT operations contexts.
Demonstrated ability to use AI enabled tools to augment analytics workflows, such as automating data validation, generating insights or summaries, supporting scenario analysis, or improving exploratory analysis.
Strong analytical thinking, attention to detail, and problem‑solving skills.
Ability to clearly communicate insights to both technical and non‑technical stakeholders.
5+ years of IT-relevant work experience with a Bachelor's degree.
OR 7+ years of IT-relevant work experience without a Bachelor’s degree.

Nice To Haves

Experience with Technology Business Management (TBM) concepts and frameworks.
Hands‑on experience with IBM Apptio, Nicus, PowerOptics or similar TBM / IT financial management tools.
2+ years of experience building and deploying AI/ML models in enterprise environments; experience supporting Finance and Accounting teams with AI or automation initiatives is strongly preferred.
Familiarity with IT budgeting, forecasting, chargeback, allocations, and cost modeling.
Experience with Power Apps, Power Automate, or similar low‑code tools.

Responsibilities

Design, build, and own IT Business Operations analytics and enablement solutions, spanning workforce management, procurement, investment governance, service performance, and IT financial management.
Lead the design, development, and maintenance of dashboards, reports, and analytical models supporting Office of the CIO insights using ITSM and TBM Platforms and related analytics tools (e.g. Excel, Power BI, Tableau, ServiceNow, Databricks, Apptio, Nicus, ProvenOptics).
Serve as the technical owner of IT Business Operations data, analytics, and AI foundations, defining data models, architectures, quality standards, and analytical patterns that enable scalable, insight driven decision making.
Apply AI and advanced analytics techniques to enhance IT operational insight, improve forecasting and modeling accuracy, and surface trends, risks and drivers across cost, capacity, performance, and demand.
Build and maintain IT budgeting and business operations planning data models, integrated with enterprise finance, HR and procurement systems, covering headcount, contracts, cost categories and other operational drivers.
Ensure accuracy, consistency, reliability, and usability of data models, input mechanisms, calculations, and reporting outputs.
Lead the technical implementation and evolution of ITFM/TBM platforms (e.g., Apptio, Nicus, ProvenOptics or similar), including data ingestion, extensible modeling, and intelligent analytics layers.
Develop data models and analytics supporting IT budgeting, forecasting, cost transparency and financial planning activities, including variance and trend analysis.
Partner with Finance, HR, Procurement and IT BOL stakeholders to align IT data models with enterprise data models, systems and processes.
Enable AI‑driven cost transparency and IT investment governance, delivering service‑based views of spend and data‑driven insights into run vs. grow investments, funding alignment, benefits realization, and portfolio performance.
Apply AI‑assisted analytics to identify trends, risks, and optimization opportunities across IT workforce, vendor spend, service delivery, and operational performance.
Identify opportunities to standardize and streamline IT business operations processes using AI and analytics, reducing manual effort, improving data quality, and increasing scalability across planning, reporting, and governance workflows to drive efficiencies and align at an enterprise level.
Leverage AI and advanced analytics techniques to enhance analytics platforms and systems, including automated data validation, intelligent summarization, forecasting, scenario modeling, and trend analysis.
Partner with Finance, HR, Procurement and IT BOLs during system transformations ensuring AI ready data structures and analytics capabilities are embedded from the start.
Develop reusable templates, data models, and documentation to improve consistency, efficiency and scalability.