AstraZeneca
Global Development Scientist, Clinical Development
India - Bangalore · full-time · hybrid
Company's own boardMaster's degree10–15 yrs
First seen Oct 10 · seen live today · from AstraZeneca's own Workday board
Skills mentioned
gcp
The posting, as published
Job Title: Global Development Scientist, Clinical Development
Career Level – E
Location: Manyata Tech Park, Bangalore
Work Type: Hybrid
Total years of experience: 10 to 15 years
Introduction to role:
The Global Development Expert in Clinical Development and AI will provide scientific and clinical input to all aspects of late-stage product development and AI-assisted ways of working. This includes but is not limited to building, delivering, and analyzing pivotal clinical trials. It also covers studies that further characterize the overall benefit, risk, and value of products in respiratory and immunology therapeutic area (TA) in late-stage development. In this role the scientist will seek input from the appropriate functional experts and will coordinate these activities in support of clinical studies and programs.
The Global Development Scientist passionate about Clinical Development and AI will focus on ensuring safety evaluations for phase II/III trials are comprehensive and efficient. They will also build and apply AI solutions to aid this effort.
The objectives for the Global Development Scientist will be established by the Global Clinical Program Lead (GCPL) in agreement with Global Clinical Head (GCH).
This position focuses on late-stage clinical trials within the Respiratory TA. The Global Development Scientist works closely with the study team physician, sites, and other collaborators in Respiratory and the wider AI community. They contribute to all aspects of scientific input, clinical data quality metrics, and safety evaluation.
Alongside delivery of the role’s established scientific and clinical responsibilities, the Global Development Scientist will act as a lead for selected AI-enabled use cases—identifying high-value opportunities, translating clinical needs into clear requirements, piloting solutions in live studies, piloting and evaluating workflows, and supporting adoption at scale.
A key purpose of the role is to support using AI-assisted methods that maintain or improve quality. These methods speed up building, conducting, reviewing data, and interpreting. The role also ensures accountable human expertise and evaluative judgment remain in clinical research and trials. Always ensuring that the novel AI solutions deployed follow appropriate governance processes and maintain the standards of Good Clinical Practice (GCP). All of this with the ultimate goal of helping to bring new treatments to patients.
The role will connect clinical domain expertise with AI capabilities. It will help establish reusable approaches rather than isolated pilots, with success assessed through evidence of adoption and measurable improvements in clinical development outcomes, quality, efficiency or cycle time.
You will be expected to collaborate effectively with colleagues in late-stage Respiratory groups, and to build productive connections. You will combine strong scientific judgement with curiosity about emerging AI methods, communicate advantages and drawbacks transparently, and support colleagues to use approved tools confidently and responsYou will present scientific and AI-enabled insights to multidisciplinary teams and key collaborators. You will also contribute as a member of a diverse, motivated team across multiple Biopharmaceutical divisions. s R&D.
About AstraZeneca:
AstraZeneca is a global, science-led, patient-focused pharmaceutical company that focuses on the research, development, and commercialisation of prescription medicines. We aim to transform the lives of patients with improved outcomes and a better quality of life. But we’re more than one of the world’s leading pharmaceutical companies. At AstraZeneca, we 're dedicated to being a Great Place to Work.
Accountabilities:
Provide scientific leadership in the innovative design, execution and interpretation of clinical trials in one or more development programs.
Effectively collaborate across other functions such as Patient Safety, Regulatory Affairs, Clinical Operations, and early development groups.
Be involved primarily in late stage (PhIIb and Phase III) clinical programs and to collaborate with clinical colleagues supporting early-stage programs as well as medical affairs colleagues.
Provide expert scientific input into the preparation of regulatory documents and interactions with regulatory authorities.
Provide expert scientific review, analysis, and interpretation of data from ongoing studies and in the literature.
Lead development of quality metrics and data review plan for assigned studies.
Identify and prioritise clinical development activities where AI assistance can add meaningful value, define the clinical problem and intended outcome, and agree fit-for-purpose success measures with study and functional partners, including stakeholder alignment, workflow integration, user feedback, training, adoption monitoring and transition from pilot to sustained use
Support and contribute to medical monitoring of trials.
Lead and participate in activities that ensure quality, consistency and integration of clinical study related deliverables and ensure safety evaluation process within the clinical team.
Provide clinical leadership for the testing and validation of AI-assisted outputs, ensuring appropriate human review, traceability, data quality, privacy, security and compliance with applicable quality and regulatory expectations, embedding fit-for-purpose methods into study and programme workflows
Ensure scientific input to TA standards.
Provide scientific evidence to support strategic decision making for R&D, marketing, clinical, and business development departments.
Present protocol and scientific results to multidisciplinary teams and key stakeholders
Develop and review protocols, informed consent, investigator’s brochure and other clinical development documents.
Organize and analyse data from clinical research to build new hypothesis.
Support upskilling in AI-enhanced working methods. Contribute to AI capability development across Respiratory Clinical Development. Engage with AI user networks and cross-functional initiatives to share learning, promote reuse, and scale AI-assisted practices.
Essential Skills/Experience:
Relevant Bachleors or Masters degree with experience from clinical development.
Three or more years of relevant pharmaceutical industry experience (multi-country clinical trials) is required.
Understanding of scientific & clinical issues related to the design and implementation of clinical trials and interpreting trial results particularly in respiratory and immunology clinical development.
Proven ability to work collaboratively in a cross-functional setting.
Experience particularly in Phase II and Phase III clinical development.
Experience using AI technologies and building or deploying AI solutions in a work environment, with demonstrated competence applying AI in clinical, biomedical or drug development settings
Strong proficiency in daily knowledge work with agentic AI tools, applying appropriate human judgement and oversight
Experience in working in GCP-compliant environments, and excellent understanding of principles of GCP
Desirable Skills/Experience:
Proven track record of leading practice change and pioneering new technologies or ways of working, with measurable impact in biomedical, clinical or drug development settings.
Excellent written and verbal communication skills, with the ability to explain new AI concepts, evidence, benefits and limitations clearly to clinical and scientific audiences.
Experience with regulatory submissions, life cycle management, advisory boards, annual safety updates.
Experience working with or implementing governance frameworks related to data and AI solutions
Experience in AI method development or in leading the build or deployment of AI solutions, with demonstrated impact in clinical, biomedical or drug development settings.
Technical expertise in modern AI methodologies and softwar