Central Operations Analytics Senior Analyst
USFull-TimeSenior
Salary84,000 - 144,900 USD per year
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Job Details
- Experience
- 3+ years of experience
- Required Skills
- SQLArtificial IntelligenceBusiness IntelligenceData AnalysisMicrosoft Power BICommunication SkillsAnalytical SkillsMicrosoft ExcelProblem SolvingCritical thinkingReportingDatabricks
Requirements
- Bachelor’s degree or equivalent experience in Business, Data Analytics, Healthcare, or a related field.
- 3+ years of experience in data analysis, reporting, or business intelligence roles.
- Strong proficiency in Excel (advanced functions such as Power Query, Power Pivot, and pivot visualization).
- Solid SQL skills (including CTEs and temporary tables), with advanced SQL preferred.
- Experience with data visualization and BI tools such as Power BI (intermediate level or higher).
- Familiarity with Databricks or similar data platforms is highly desirable.
- Healthcare revenue cycle experience is a strong advantage.
- Strong analytical, problem-solving, and critical thinking skills with attention to detail.
- Ability to manage multiple priorities in a fast-paced, deadline-driven environment.
- Excellent communication skills with the ability to collaborate effectively across technical and non-technical stakeholders.
- Curiosity and openness to innovation, including the use of emerging technologies such as AI.
Responsibilities
- Develop, monitor, and analyze operational data and KPIs to identify trends and deliver actionable insights supporting business performance.
- Design, build, and maintain recurring and ad-hoc reports using SQL, Excel, and BI tools to support operational and leadership decision-making.
- Create reusable SQL templates and optimize data workflows within Databricks and other analytics platforms.
- Conduct testing and validation of reporting components to ensure accuracy, consistency, and reliability of outputs.
- Collaborate with business and operations stakeholders to understand needs and translate them into effective analytical solutions.
- Support continuous improvement efforts by identifying process inefficiencies and recommending data-driven enhancements.
- Provide training and guidance to co-workers and leaders on analytics tools, reporting systems, and data interpretation.
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