Position: Clinical Business Analyst
Location: New York, NY 10037
Duration: November 16, 2026 – January 9, 2027
Schedule: Monday–Friday, 37.5 hours/week, 7.5 hours/day
Shift: 8:00 AM–4:00 PM or 9:00 AM–5:00 PM
Work Arrangement: Onsite only
Employment Type: Temp-to-hire; candidates must be interested in converting to a full-time employee
Salary Range: $70,000–$100,000 annually, based on experience
Pay Rate: $60/hr.
Requirements
Required Experience & Education
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Bachelor’s or Master’s degree in Computer Science, Informatics, Analytics, or a related field, plus at least 1 year of relevant experience; or
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4 years of experience in data analytics, software programming, or a related field.
Required Skills
Additional Skills
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Tableau and data analytics
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Advanced Excel and Microsoft Office
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Healthcare data and Epic experience
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Data modeling and software programming
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Financial reconciliation and financial planning
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Business requirements analysis and process documentation
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Flowchart creation and conceptual data process modeling
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Process improvement and performance optimization
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Data validation, integrity, and quality assurance
Responsibilities
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Build and maintain data infrastructure, pipelines, and automated processes to extract, load, and transform data from multiple sources using SQL, Python, and other technologies.
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Provide analytics to support operational and business decisions across value-based purchasing (VBP), revenue and expense, ambulatory care, and other domains.
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Assemble raw and disconnected datasets and transform them into efficient data models for tracking, reporting, and financial operations.
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Identify, design, and implement process improvements, automate manual processes, and optimize operational efficiency.
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Collaborate with cross-functional stakeholders and partners to resolve data-related issues and support departmental needs.
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Prepare ad hoc and recurring reports, analyses, and analytical tools to support senior management and executive decision-making.
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Create reports and dashboards using Epic data to provide visibility into key metrics and trends.
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Develop routine data validation rules and processes to ensure data completeness and integrity.
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As