Senior Data Analyst
New
T
Tria FederalFederal Healthcare
100% Remote within the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5 to 8+ years
- Required Skills
- PythonSQLBusiness IntelligenceData AnalysisMicrosoft Power BIData visualizationStakeholder managementR
Requirements
- Bachelor’s degree in a quantitative, analytical, technical, or related field.
- 5 to 8+ years of professional experience in data analysis, business intelligence, or analytics consulting.
- Mastery of advanced SQL, including joins, window functions, and query optimization.
- Strong proficiency in Python and/or R for data manipulation, analysis, and automation.
- Experience developing dashboards and visual analytics in Power BI or comparable BI tools.
- Proven ability to analyze large, complex, and sometimes imperfect data sets.
- Strong business acumen with ability to connect data findings to operational outcomes.
- Excellent written and verbal communication skills.
- Proven ability to lead analytic tasks or workstreams with minimal supervision.
- Experience mentoring or reviewing the work of junior analysts.
Responsibilities
- Lead complex data analysis efforts supporting VHA program operations, performance management, reporting, and executive decision-making.
- Develop, optimize, and maintain advanced SQL queries, data extracts, reporting logic, and analytical data sets from large and complex data sources.
- Use Python and/or R to perform data cleaning, transformation, statistical analysis, automation, validation, and repeatable analytics workflows.
- Design and deliver dashboards, scorecards, and visual analytics using tools such as Power BI or similar BI platforms.
- Translate business questions into analytical approaches, measurable indicators, and clear findings for technical and non-technical audiences.
- Partner with government stakeholders, program managers, subject matter experts, engineers, and data teams to define requirements and deliver high-quality analytic products.
- Identify trends, anomalies, risks, operational inefficiencies, and opportunities for process improvement through rigorous data analysis.
- Support data quality assessment, reconciliation, validation, documentation, and governance activities.
- Prepare executive-level briefings, written summaries, visualizations, and recommendations that communicate complex findings clearly and concisely.
- Contribute to project planning, estimation, prioritization, and delivery management for analytics-related tasks and workstreams.
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