Director of Oncology Clinical Intelligence & Real-World Evidence

AstraZeneca; Gaithersburg (MD); Hybrid; USD 122,000 - 160,000; Full time

Benefits offered by this job

Short-term incentive bonus

Equity-based long-term incentive

401(k) plan

Paid vacation and holidays

Health benefits

Job summary

AstraZeneca is seeking a technical specialist in clinical intelligence and real-world evidence to translate complex data into decision-ready insights for Hematology/Oncology. The role partners with Global Product Teams to shape evidence generation strategies and advance Phase 3 investments and patient access.

You will build multimodal patient models, work with external control arms, and apply causal inference and ML within regulated HTA frameworks, leveraging Python, R, and SQL in cloud

Qualifications

• Advanced degree (PhD or equivalent) in a quantitative field.
• Strong causal inference methods and observational study design.
• Hands-on ML and multimodal modeling experience.
• Experience with external control arms or trial simulators.
• Knowledge of regulatory/HTA evidentiary standards.
• Proficiency in Python, R, and SQL; cloud analytics familiarity.

Responsibilities

• Prioritize evidence needs across hematology/oncology product lifecycle.
• Apply ML and causal inference to patient stratification.
• Build multimodal patient models from diverse data.
• Produce decision-ready insights for development and access.
• Collaborate with platform teams to enable new tools.
• Bridge strategic evidence with technical delivery.

Skills

Causal inference

Multimodal modeling

Observational study design

Machine learning

External control arms

Regulatory/HTA

Education

PhD or equivalent in a quantitative field

Tools

Python

R

SQL

Job description

AstraZeneca is seeking a technical specialist in clinical intelligence and real-world evidence to translate complex data into decision-ready insights for Hematology/Oncology. The role partners with Global Product Teams to shape evidence generation strategies and advance Phase 3 investments and patient access.

You will build multimodal patient models, work with external control arms, and apply causal inference and ML within regulated HTA frameworks, leveraging Python, R, and SQL in cloud