Diagnostic Strategy Senior Director - AI

• About AstraZeneca

At AstraZeneca, we are committed to pushing the boundaries of science to deliver life-changing medicines to patients worldwide. As a global biopharmaceutical leader, our focus on innovation and collaboration drives us to transform the treatment of complex diseases, including cancer. We are seeking a dynamic leader to join us as the Diagnostic Strategy Senior Director, AI and Multimodal, leading the development and implementation of early-stage, pre-launch commercial diagnostic strategy across multiple tumor types, brands and indications in the AI/multimodal Dx space.

Reporting into the Head, Strategy & Partnerships – Global Oncology Diagnostics, this role has specific responsibility for developing a commercial strategy towards AI-enabled and multimodal biomarker/diagnostic solutions – spanning software as a medical device (SaMD) and integrating other diagnostic platform data, leading the development and implementation of early-stage, pre-launch commercial diagnostic strategy across multiple tumor types, brands and indications in a given area, so that future AI/multimodal patient-identification approaches align with AstraZeneca’s oncology strategy.

The strategy and implemented activities will account for global markets’ future diagnostic requirements, providing internal and external thought-leadership, educational tools, and developing diagnostic platforms and novel solutions to facilitate the timely and successful execution of future diagnostic launches. As projects mature and new indications are added, the expectation of the Senior Director is to expand the strategy to encompass new and additional opportunities.

As a key leader and member of cross-functional teams, the post holder is accountable for progressing strategic initiatives and projects to deliver diagnostic solutions in-market. They will lead governance processes, develop business cases, and spearhead senior leader engagement in their area, as well as enabling successful hand-over of projects to the diagnostic marketing team as indications approach launch.

Typical Accountabilities:

• Craft detailed commercial deployment plans for AI and multimodal diagnostic tools, as a part of international cross-functional teams
• Build novel internal capabilities and scalable processes for the commercial deployment of AI and multimodal patient-identification solutions across the oncology portfolio
• Provide day-to-day program oversight for AI-enabled and multimodal diagnostic projects, coaching and mentoring cross-functional team members
• Act as internal lead of working teams, pulling together in particular Oncology Data Science and AI, Commercial Digital Health, Regulatory/SaMD, Data Science, Precision Medicine and other stakeholders for the technical, commercial and corporate evaluation of AI and multimodal diagnostic strategy opportunities and their execution into the market
• Design, launch and oversee multiple AI/multimodal diagnostic collaborations and pilot programs with external partners, ensuring alignment with regulations and future market directions
• Actively contribute and collaborate with the broader AZ oncology diagnostics team to provide diagnostic inputs, strategy and solutions into the wider Oncology Business Unit for a given portfolio of projects, including being a key member of relevant teams, such as tumor franchise teams, tumor councils, GPTs, and IBTs
• Work collaboratively and flexibly to accommodate the various routes through which projects of different natures may arise, including alongside Global Diagnostic Partnerships, Marketing, Market Access and Scientific Affairs colleagues, to identify in-market diagnostic solutions
• Collaborate with Diagnostic Scientific Affairs and Medical Affairs to deliver cross-portfolio diagnostics-related evidence needs (such as analytical concordance data, real-world evidence, piloting technologies)
• Develop diagnostic strategic expertise in regional and local teams and remove barriers to future portfolio testing needs through external engagement, such as with lab networks, Key External Experts (KEE), and with diagnostic companies (alongside partnerships colleagues)

Education, Qualifications, Skills and Experience:

Essential:

• Minimum of 5 years focused on AI-enabled and/or multimodal oncology biomarkers specifically
• Experience establishing or scaling novel AI/multimodal diagnostic capabilities, ideally in a clinical implementation setting, and managing partnerships to do so
• Doctorate, MD or equivalent education with demonstrable expertise in computational biology, bioinformatics, computer science or a closely-related AI field, providing credibility to scientific audiences
• Proven knowledge of clinical diagnostic workflows across molecular, histopathology and imaging modalities, plus strong enthusiasm for the intersection of biology, data and technology
• Thorough understanding of the diagnostics environment, including development and commercialization of multiple types of diagnostic tests, as well as complexities in global markets in relation to diagnostics test access and adoption
• Broad knowledge of pharmaceutical and diagnostic company businesses, processes and activities, and an established wide external network of experts in the AI and multimodal biomarker space
• Knowledge of scientific, commercial and financial evaluation techniques. Strong analytical skills and ability to ascertain the relevant issues from large masses of information

Desirable:

• Demonstrated capability in leading diverse teams, setting direction, mentoring talent and delivering impact at senior organizational level
• Strong leadership attributes to set direction, generate commitment, balance short- and long-term needs, constructively resolve issues
• Project-management experience including experience of diagnostics commercialization and launch, working with third-party companies
• A working understanding of diagnostic regulatory frameworks worldwide
• Familiarity with phase-gate assay and IVD/companion-diagnostic development, FDA and EU regulatory submissions for SaMD, and Good Machine-Learning Practice (GMLP)
• Understanding of software-development lifecycles, data standards for ‑omics integration, natural-language-processing tools and the use of electronic medical records in real-world evidence generation
• Experience working on establishing access to diagnostics, i.e. in partnering with patient groups, regulatory groups and payers

Date Posted

29-Aug-2025

Closing Date

28-Sep-2025

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.