Precision Medicine Group - Senior Data Analyst
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Requirements
• Minimum 5 years’ experience, with 3+ years in relevant analytics roles. • Bachelor’s/Master’s in Computer Science, Electronics, Pharmacy, Life Sciences, Data Science, Statistics or related field. • Prior Experience with structured datasets: DRG, Symphony, IQVIA, McKesson. • Strong proficiency in SQL, Python, Excel, PowerPoint. • SQL, Python, Excel, PowerPoint • Experience in Pharma/life-science consulting or analytics agencies. • Exposure to RWE sources including EHR/EMR, CMS datasets. • Understanding of LoT frameworks, treatment guidelines and market-access structures. • Working knowledge of Python and visualisation tools (Power BI, Tableau). • understanding of data modeling and statistical techniques. • data modeling • Client-facing experience with ability to translate analytics into business insights. • Therapy-area familiarity (oncology, immunology, rare diseases). • Experience conducting stakeholder workshops or building interactive dashboards. • Experience working with global teams and multi-geography datasets. • Any data provided as a part of this application will be stored in accordance with our Privacy Policy. For CA applicants, please also refer to our CA Privacy Notice.
Responsibilities
• Lead and execute analytics projects focused on patient-journey and line-of-therapy mapping, Brand analytics. • Analyze structured claims and patient datasets such as DRG, IQVIA, McKesson, Symphony claims. • Conduct exploratory data analysis (EDA) to assess treatment patterns, pathways and utilization. • Support HEOR/HCRU analyses including prevalence, burden, incidence and cost-of-illness studies. • Develop and present client-facing insights using dashboards, PowerPoint and visual analytics. • Build and optimise SQL queries, pipelines; use Excel and Python for automation and analysis. • Collaborate with HEOR, market-access, strategy and engineering teams. Ability to gather requirements, articulate approach, timeline and execution with key stakeholders are of equal importance. • Ensure data integrity, governance, documentation and reproducibility. • Independently manage workload, communicate progress and drive project delivery.
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