Associate Director, Translational Data Science – Hematology R&D
Listed on 2026-03-02
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IT/Tech
Data Science Manager, Data Analyst
Job Title: Associate Director, Translational Data Science – Hematology R&D
Location: South San Francisco, California, United States
At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. If you are swift to action, confident to lead, willing to collaborate, and curious about what science can do, then you’re our kind of person.
Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face‑to‑face in our offices 3 days a week
. Our head office is purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects.
Our dedication to sustainability is also central to our culture and part of what makes AstraZeneca a great place to work. We know the health of people, the planet and our business are interconnected which is why we’re taking ambitious action to tackle some of the biggest challenges of our time, from climate change to access to healthcare and disease prevention.
Introductionto Role
AstraZeneca’s Translational Data Science, Haematology R&D team is seeking an Associate Director passionate about driving strategic insights from sophisticated clinical and molecular data to support our hematology therapeutic portfolio. This role is based at AstraZeneca’s South San Francisco site, and will anchor translational data initiatives across clinical programs, as well as contribute to evidence generation advises forms clinical decision-making and accelerates patient impact.
As an individual contributor you will be a hands‑on data science expert, responsible for developing reproducible analytical methods and data products. You will apply domain knowledge in hematology, clinical trial data standards, and modern analytical frameworks to enable robust interpretation and communication of translational results.
You will work at the intersection of clinical development, biomarkers, biostatistics and data engineering, collaborating across functions to improve the quality, accessibility and scientific utility of translational and clinical datasets, and you will mentor junior colleagues.
Accountabilities- Lead the design, implementation and validation of analytical workflows for translational and clinical trial data to generate actionable insights for hematology indications.
- Apply expertise in clinical data domains (including but not limited to ADaM and SDTM formats) to support data readiness for statistical analysis, regulatory deliverables and clinical reporting.
- Develop and maintain reproducible data transformation pipelines, quality‑controlled datasets, and visualization tools that support cross‑functional decision making.
- Collaborate with clinical operations, biostatistics, biomarker science and data engineering partners for decision support and to harmonize data standards and improve data interoperability.
- Interpret sophisticated data outputs and contribute to strategic planning, clinical study reports, regulatory documents and scientific communications.
- Mentor junior data scientists and analysts; provide technical guidance and promote adoption of standard processes in translational analytics.
- Serve as a subject matter expert and resource for hematology translational data analytics, with the ability to clearly communicate findings to scientific and clinical audiences.
- Advanced degree (PhD preferred) in a quantitative field (Biostatistics, Bioinformatics, Data Science, Computational Biology, or similar).
- 6+ years of proven experience in translational data science with a PhD, clinical analytics or related data roles within biopharma (Master’s Degree: 8+ years of experience).
- Demonstrable expertise working with clinical trial datasets, with strong familiarity with clinical data standards such as ADaM and SDTM to support both analysis and regulatory submission readiness in drug development programs.
- Prior…
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