Senior Analyst

Carnegie Museums of Pittsburgh


Website CarnegieMembers Carnegie Museums of Pittsburgh

Four Distinctive Museums

The Senior Analyst (Power BI) builds scalable data models, cleans and transforms data, and deploys data visualizations, reports, and dashboards that provide key insights to the organization for fundraising success. The Senior Analyst is a data storyteller that conducts descriptive, exploratory, and predictive data analyses.


  • Bachelor’s degree in a quantitative field of study, such as Data Science, Analytics, Mathematics, Statistics, Research, Computer Science, Information Systems, Engineering, Economics
  • 3 years of experience developing Microsoft Power BI dashboards and data models, utilizing DAX, Power Query, Pipelines, Paginated Reports, and/or DAX Studio required
  • Microsoft Certified Data Analyst (Exam-DA 100) certification a plus
  • 1 year of experience with SQL preferred.


  • Strong analytical skills.
  • Microsoft Power BI Dashboards: design and implementation.
  • SQL experience preferred.
  • Understanding of ETL/Data Warehousing preferred.
  • Proficiency in a statistical programming language (R/Python) a plus.
  • Experience with Raiser’s Edge or Crystal Reports a plus.
  • Comfortable working independently and in a team environment to execute assigned deliverables in a prompt and efficient manner.
  • Excellent communication skills; diplomacy and persuasive abilities.
  • Excellent written and verbal communication skills.


  • Extracts, transforms, loads, validates, models, analyzes, reports, and visualizes data.
  • Conducts descriptive, exploratory, and predictive data analyses.
  • Creates Power BI deployment models and dashboards, connecting data from SQL Server databases.
  • Conducts load testing on Power BI dashboards. Troubleshooting performance bottlenecks.
  • Establishes KPIs to measure the effectiveness of the museum’s fundraising operations
  • Evaluates historical fundraising performance and forecast future performance.
  • Develops and directs the implementation of strategies to substantially improve data processing efficiencies.
  • In partnership with leadership, identifies what ifs and improvement opportunities and subsequently perform analysis to quantify and validate.
  • Other duties as assigned.

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