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Strategic Oncology Analytics Specialist
7 days ago
At MSD, we are innovating the way we understand our patients and their needs through the Human Health Digital Data and Analytics (HHDDA) team. We work cross-functionally to invent new ways of engaging with our customers and patients using digital, data, and analytics while measuring their impact.
About the RoleWe are seeking a Senior Specialist, Oncology New Products, Oncology Global Commercial Pipeline Analytics, HHDDA who will be responsible for developing and delivering data and analytics, generating strategic insights, and addressing key business questions from the Global Oncology New Products Marketing team to inform current and future pipeline strategies.
Main Responsibilities:- Pipeline Analytics & Insights: Conduct analytics and synthesize insights to enable launch excellence for multiple new assets.
- Analytics Delivery: Hands-on analytics project delivery with advanced expertise in data manipulation, analysis, and visualization using tools such as Excel-VBA, SQL, R, Python, PowerBI, ThoughtSpot or similar technologies and capabilities.
- Benchmarking Analytics: Lead benchmarking analytics to collect, analyze, and translate insights into recommended business actions to inform strategic business choices.
- Stakeholder Collaboration: Partner effectively with global marketing teams, HHDDA teams, and other cross-functional teams to inform strategic decisions and increase commercial rigor through all phases of pipeline asset development.
- Bachelor's degree, preferably in a scientific, engineering, or business-related field.
- Overall experience of 8+ years, with 4+ years of relevant experience in oncology commercialization, advanced analytics, oncology forecasting, insights syndication, clinical development, or related roles within the pharmaceutical or biotechnology industry.
- Therapeutic area experience in Oncology and/or emerging oncology therapies.
- Strong problem-solving abilities, to find and execute solutions to complex or ambiguous business problems.
- Experience conducting predictive modelling and secondary data analytics on large datasets using relevant skills (e.g., excel VBA, Python, SQL) and understanding of algorithms (such as regressions, decision trees, clustering etc.).
- Deep understanding of commercial Oncology global data ecosystem e.g., Epidemiology datasets, claims datasets, and real-world datasets.