(Senior) Medical Director, Oncology Life Sciences Research
Posted Sep 14, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
Tell me about your clinical experience in GI or breast cancers and how it shapes the way you think about drug development.
What they are checking: Whether their bedside experience translates into credible judgment about trial design and unmet need.
Tell me about a time you translated a messy clinical problem into a clear data question someone could actually answer.
What they are checking: Whether they can bridge physicians and data scientists, which is the core of a role between clinic and data.
Describe a time you had to influence senior people at a client who outranked you in their own organization.
What they are checking: Whether they can lead through expertise and preparation when they have no formal authority.
What would you do
A biopharma partner is struggling to enroll a GI cancer trial. How would you use real-world data to help them?
What they are checking: Whether they can turn feasibility, site selection and patient-finding into concrete actions using multimodal real-world data.
What would a long-term clinical strategy for a key pharma account look like, and how would you build it?
What they are checking: Whether they think past one project to how the partnership grows over years across data, AI tools and trials.
An account team wants you to back a claim to a client that you think the data does not quite support. What do you do?
What they are checking: Whether they protect scientific integrity under commercial pressure, since their credibility is the asset they bring.
How do you prioritize when several account teams all want your time on the same week?
What they are checking: Whether they can triage requests by impact and say no clearly without damaging internal relationships.
About the work
How would you explain the strengths and limits of real-world evidence to a pharma team used to randomized trial data?
What they are checking: Whether they can speak honestly about bias, missingness and confounding while still showing where the data adds value.
How do you see agentic AI tools changing the way biopharma teams run oncology research?
What they are checking: Whether they have a grounded view of AI that neither dismisses it nor oversells what it can do today.
How would you stay current on breast and GI oncology while working outside daily clinical practice?
What they are checking: Whether they have a real plan to keep their clinical knowledge sharp, since stale expertise loses clients' trust.
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As published by Tempus AI.