Associate Director, Oncology Clinical Intelligence and Real World Evidence

AstraZeneca • Gaithersburg, MA

2d • Hybrid

About The Position

AstraZeneca is hiring an Associate Director to turn complex clinical and real-world data into evidence that informs pivotal decisions in Hematology/Oncology. The role combines portfolio-level evidence prioritization with hands-on analytics, helping stakeholders identify high-value evidence gaps and deliver analyses that support Phase 3 investment decisions, trial design, development strategy, and patient access.

As a technical specialist in clinical intelligence and real-world evidence, the Associate Director will apply machine learning, causal inference, and multimodal modeling to produce decision-ready insights. The work includes developing patient-level models, external control arms, and other analyses using clinical, genomic, imaging, and real-world data. The role also contributes to persistent Hematology-specific intelligence and collaborates across functions to align evidence generation with development, regulatory, and access milestones.

The position follows AstraZeneca's hybrid working approach, with employees engaging face-to-face in offices three days per week. The annual base pay range is $122,121.60–$160,284.60, with a short-term incentive bonus opportunity and eligibility for an equity-based long-term incentive program. Benefits include a qualified retirement program, paid vacation and holidays, paid leaves, and health benefits, including medical, prescription drug, dental, and vision coverage.

Requirements

• PhD or equivalent advanced degree in a quantitative discipline such as epidemiology, biostatistics, computational biology, machine learning, health data science, or a related field.
• Strong methodological foundation in causal inference and observational study design, including propensity score methods, instrumental variables, target trial emulation, and comparative effectiveness research.
• Hands-on experience with machine learning and multimodal modeling, including supervised and unsupervised methods, deep learning for imaging or molecular data, and integration of heterogeneous data into patient-level models.
• Experience building or contributing to external control arms, trial simulators, or prognostic models using real-world and/or clinical trial data.
• Understanding of regulatory and health technology assessment evidence standards, and ability to design analyses that meet evidentiary requirements for submissions and payer engagement.
• Proficiency in Python, R, and SQL.
• Familiarity with cloud-based analytics environments.

Nice To Haves

• Domain expertise in hematology or oncology and familiarity with disease-specific endpoints, pathways, and standards of care.
• Track record of influencing cross-functional strategy with evidence and engaging product and clinical leaders to drive decisions.
• Experience deploying analytics into clinical trial operations, submissions, or payer engagements.
• Publications, conference presentations, or open-source contributions in causal inference, multimodal modeling, or real-world evidence.
• Hands-on experience with cloud platforms and MLOps practices to scale models and pipelines.
• Experience integrating digital endpoints, pathology AI, or biomarker panels into evidence strategies.
• Ability to design reusable data and model assets that generalize across indications and studies.

Responsibilities

• Partner with Hematology/Oncology stakeholders and Global Product Teams to identify and prioritize evidence needs across the product lifecycle, including Phase 3 investment decisions, subpopulation discovery, and trial design.
• Apply machine learning and causal inference to patient stratification, external control arm construction, prognostic risk adjustment, and treatment-effect heterogeneity analyses, ensuring analyses meet regulatory and HTA expectations.
• Deliver and validate patient-level models integrating clinical, genomic, imaging, and real-world data for clinical-trial or routine-care use, emphasizing reproducibility and rigorous validation.
• Translate internal and competitor trial data and real-world data into insights on standard of care, patient pathways, benchmarking, and unmet need to inform development and access strategies.
• Work with platform and tooling teams to incorporate new tools, agents, and experimental approaches into evidence generation, and build Hematology-specific intelligence for the Phase 3 Investment Decision Intelligence Foundation.
• Align technical evidence delivery with development, regulatory, and access milestones.
• Collaborate with Translational Science and Clinical Development to incorporate signals such as digital endpoints, pathology AI, and biomarker panels.

Benefits

• Qualified retirement program (401(k) plan).
• Paid vacation and holidays.
• Paid leaves.
• Health benefits including medical, prescription drug, dental, and vision coverage.
• Short-term incentive bonus opportunity.
• Eligibility to participate in an equity-based long-term incentive program.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Ph.D. or professional degree