Associate Manager / Manager, Lung Cancer Commercial Analytics

Role Overview:
We are seeking a highly analytical and confident Associate Manager/Manager to support Commercial Analytics for the Lung Cancer portfolio, including both ICLC and NSCLC. This role will lead market sizing, patient analytics, and launch analytics, with increasing responsibility for advanced data science and predictive modeling as the program evolves. The ideal candidate is a strong communicator who can operate independently and deliver high‑quality insights to stakeholders with varying levels of technical expertise.
Key Responsibilities
Lung Cancer Market & Opportunity Analytics

• Build and maintain market sizing models for lung cancer indications (ICLC and NSCLC).
• Develop launch analytics frameworks to support commercial strategy, early‑market planning, and competitive positioning.
• Analyze epidemiology, incidence, prevalence, and treatment pathways to quantify market potential.

Patient Analytics 

• Conduct patient journey analytics, including diagnosis, treatment initiation, switching, and progression.
• Leverage claims, EMR/EHR, and real‑world datasets to identify patient segments and unmet needs.
• Generate insights to inform targeting, segmentation, and commercial decision‑making.

Cross‑Functional Collaboration

• Work closely with commercial leads, medical teams, and external vendors to ensure analytical accuracy and strategic alignment.
• Present insights confidently to senior stakeholders with varying levels of technical expertise.
• Operate independently in a high‑expectation environment, providing proactive recommendations.

Qualifications:
Required

• 5–6 years of pharmaceutical analytics experience (commercial, patient analytics, or oncology preferred).
• Strong experience with market sizing, patient analytics, and launch analytics.
• Familiarity with lung cancer datasets and oncology analytics (ICLC, NSCLC).
• Ability to work independently and communicate insights clearly to non‑technical stakeholders.
• Strong analytical tools experience (SQL, Python, R, or similar).

Preferred

• Experience with real‑world data (claims, EMR/EHR).
• Exposure to predictive modeling or data science techniques.
• Prior experience supporting oncology commercial teams.