Business Data Analyst

This role is Hybrid, 3 days a week on-site to any UL Office in the US.

The Data Analyst, Project Management position supports Global Operations by turning complex internal and external data into clear insights that improve project planning, execution, governance, and decision-making. This role partners with project managers, operational leaders, finance, data engineering, and cross-functional stakeholders to undertake research, collect and analyze data, prepare studies, develop and maintain datasets, dashboards and reports, support business cases, identify risks and opportunities, and provide actionable insights that enable effective delivery of global strategic initiatives.

• Develop and maintain dashboards, reports, trackers, and visualizations that provide clear visibility into project performance, milestones, risks, financials, resources, and operational outcomes.

• Analyze project, operational, financial, and business data to identify trends, gaps, risks, dependencies, and opportunities that support timely decision-making across Global Operations.

• Support project managers and operational leaders with data analysis for project intake, prioritization, business cases, portfolio reviews, governance forums, and executive reporting.

• Collect, clean, validate, and integrate data from multiple sources to ensure accurate, consistent, and reliable information for analysis and reporting.

• Undertake research and prepare studies by collecting, reviewing, and analyzing internal and external data, including economic, technological, industry, customer, competitor, market, and operational information.

• Translate complex data into concise insights, summaries, and recommendations for technical and non-technical stakeholders.

• Partner with finance and business stakeholders to support cost-benefit analysis, ROI tracking, budget monitoring, and benefit realization for strategic initiatives.

• Support Agile and project management practices by maintaining work items, status updates, action logs, issue logs, RAID logs, and delivery metrics in relevant tools.

• Identify opportunities to improve reporting processes, automate recurring analysis, strengthen data quality, and enhance project governance.

• Collaborate with data engineering, development, and business teams to define data requirements and improve access to reliable project and operational data.

• Follow UL Solutions’ Code of Conduct and all applicable data governance, physical security, digital security, and compliance practices.

Skills and Behaviors for Success

• Strong analytical mindset with the ability to connect data, business context, and project outcomes.

• Clear communicator who can simplify complex analysis for senior leaders, project teams, and operational stakeholders.

• Detail-oriented and disciplined in data validation, documentation, follow-through, and quality of deliverables.

• Collaborative working style with the ability to build trust across functions, regions, and levels of the organization.

• Curious and proactive in identifying better ways to organize, analyze, visualize, and use data to support project delivery.

• Comfortable working in a fast-paced, global environment with multiple priorities, shifting deadlines, and ambiguity.

• Outcome-focused, with a practical understanding of how analytics supports execution, operational excellence, and business impact.

Experience, and Education

• Bachelor’s degree in Data Analytics, Business Analytics, Statistics, Mathematics, Finance, Computer Science, Information Systems, Engineering, Project Management, or a related field; equivalent experience may be considered.

• Typically 3 or more years of experience in data analysis, business intelligence, project analytics, operational analytics, or a related role.

• Experience supporting project management, program management, business operations, strategic initiatives, or portfolio reporting preferred.

• Strong proficiency with Microsoft Excel and Power BI; experience with Power Query, DAX, Tableau, or similar visualization tools preferred.

• Working knowledge of SQL, data modeling, data validation, and data integration concepts; Python or R experience is a plus.

• Familiarity with project management and collabor