Senior Director, Oncology Analytics & Clinical Intelligence

AstraZeneca; Waltham (MA); On-site; USD 145,000 - 217,000; Full time

Job summary

AstraZeneca is seeking a senior quantitative scientist to turn complex real-world and clinical data into evidence guiding Phase 3 investments, trial design, and patient access. The role emphasizes causal inference, multimodal modeling, and regulatory-ready analyses in oncology, with emphasis on reproducibility and impactful decision support.

The position involves collaboration across Hematology teams, platform and tooling groups, and Translational Science to embed AI-powered insights into

Qualifications

• PhD or equivalent in a quantitative field (e.g., epidemiology, biostatistics, computational biology).
• 5+ years in evidence strategy, RWE or advanced analytics/Data science.
• Strong causal inference and observational design foundations.
• Hands-on ML and multimodal modeling with heterogeneous data.
• Experience building external control arms or trial simulators.
• Understanding regulatory and HTA evidence standards.
• Proficiency in Python, R, SQL; familiarity with cloud environments.

Responsibilities

• Prioritize evidence gaps with Hematology stakeholders and global teams across product lifecycle.
• Apply ML and causal inference to patient stratification and trial design questions.
• Develop multimodal patient models integrating clinical, genomic, imaging, and real-world data.
• Produce decision-ready insights on care pathways, benchmarking, and unmet needs.
• Collaborate with platform teams to deploy new analytics tools and AI approaches.
• Align outputs with regulatory, development, and access milestones; engage Translational Science and Clinical Development.

Skills

Python

R

SQL

Causal inference

ML/DL

Cloud platforms

External control arms

Education

PhD or equivalent in quantitative field

Tools

Python

R

SQL

Cloud tooling

Job description

AstraZeneca is seeking a senior quantitative scientist to turn complex real-world and clinical data into evidence guiding Phase 3 investments, trial design, and patient access. The role emphasizes causal inference, multimodal modeling, and regulatory-ready analyses in oncology, with emphasis on reproducibility and impactful decision support.

The position involves collaboration across Hematology teams, platform and tooling groups, and Translational Science to embed AI-powered insights into