Business Intelligence Specialist

Description Provide advanced analytical support for a performance strategy and analytics team for a university medical system. Lead complex business intelligence projects working with department leaders and business owners to enhance clinical and business processes and support quality and performance improvement. Provide advanced data analysis and data solutions based on clinical, financial, and other data sources using analytical tools. Organize analytics teams to collect information, provide support for clinical dashboards, provide performance improvement-related information to committees and groups, and provide analytics support for setting and tracking clinical goals in collaboration with senior executive leaders, and provide analytics support on projects related to the development and execution of performance strategies and objectives. Perform quality assurance and validation on data and deliverables. Provide training for junior team members in the department, including mentorship and participation in curriculum building. Salary Range: $47.30 - 102.78/hr Qualifications Bachelor's degree in statistics, data science, business, engineering or a related quantitative field. 18 months of experience in job offered, or as a data analyst, data engineer, or a related occupational title. Demonstrated advanced proficiency in SQL, including window functions and recursive queries, as well as in Python or R for data science. Demonstrated experience applying statistical analysis and quantitative methods in healthcare settings. Demonstrated experience in developing interactive dashboards and creating data visualizations using Power BI and Tableau. Advanced analytical and quantitative skills demonstrated through expertise in mathematical and statistical methods, including multivariate analysis, time series forecasting, hypothesis testing, and experimental design and optimization techniques. Demonstrated knowledge of Machine Learning & AI, including supervised and unsupervised learning (e.g., regression, classification, clustering), natural language processing (NLP), and ensemble methods (e.g., Random Forest). Demonstrated expertise in business and strategic analytics with proven ability to perform predictive modeling to forecast business outcomes and conduct customer segmentation and lifetime value analyses. Demonstrated experience developing simulation models in a healthcare setting. Experience overseeing all phases of project management. Demonstrated experience completing projects that require critical thinking and problem-solving. Demonstrated experience working with Excel and PowerPoint. Experience working independently with minimal supervision while meeting deadlines for multiple projects with shifting priorities. Demonstrated ability to effectively communicate in oral and written communications. #J-18808-Ljbffr