Senior Data Analyst
New
Flexible remote work arrangement within IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years of overall experience, including at least 3+ years in data analytics roles within healthcare, pharma, or life sciences domains.
- Required Skills
- PythonSQLData AnalysisMicrosoft ExcelPowerPoint
Requirements
- 5+ years of overall experience, including at least 3+ years in data analytics roles within healthcare, pharma, or life sciences domains.
- Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, Life Sciences, Pharmacy, Engineering, or related fields.
- Strong hands-on experience working with structured healthcare datasets such as DRG, IQVIA, McKesson, or Symphony claims.
- Advanced proficiency in SQL, Python, Excel, and PowerPoint for analysis and reporting.
- Solid understanding of real-world evidence (RWE) sources such as EHR/EMR and CMS datasets.
- Familiarity with line-of-therapy frameworks, treatment guidelines, and healthcare market access structures.
- Experience in pharma consulting, analytics firms, or life sciences data environments is highly preferred.
- Strong communication skills with the ability to translate complex data into clear business insights for clients.
Responsibilities
- Lead analytics initiatives focused on oncology patient journeys, line-of-therapy mapping, and brand performance using large structured healthcare datasets.
- Perform exploratory data analysis to identify treatment patterns, utilization trends, and real-world clinical pathways.
- Analyze and interpret complex claims datasets such as DRG, IQVIA, McKesson, and Symphony to generate actionable insights.
- Support HEOR and HCRU studies including incidence, prevalence, cost-of-illness, and disease burden analysis.
- Build, optimize, and automate data pipelines and SQL queries while leveraging Python and Excel for advanced analysis.
- Develop dashboards and client-ready presentations using PowerPoint and visualization tools to communicate insights effectively.
- Collaborate with cross-functional teams to define analytical approaches, clarify requirements, and ensure timely delivery of insights.
- Ensure data accuracy, governance, documentation, and reproducibility across all analytical outputs.
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