AI/ML Senior Associate Scientist

<p><b><b>ROLE SUMMARY</b></b></p><p>As a core member of our AI/ML, Quantitative &amp; Digital Sciences (AQDS) team, you will:</p><ul><li>Design, implement, and maintain full-stack applications that integrate advanced Machine Learning (ML) techniques with internal and external data sources.</li><li>Develop and apply generative AI techniques using large language models (LLMs) to automate the generation of essential clinical trial documents.</li><li>Collaborate with cross-functional teams to architect and develop scalable, cloud-native microservices and APIs for AI/ML tools aimed at optimizing patient recruitment, site selection, and clinical trial management, incorporating generative AI capabilities to streamline authoring workflows.</li><li>Leverage modern front-end frameworks (e.g., React, Angular, Vue) to build intuitive user interfaces that provide real-time insights from ML models and facilitate decision-making for clinical operations, including AI-generated document review and customization.</li><li>Work closely with DevOps and data engineering teams to streamline CI/CD pipelines, automate infrastructure as code (IaC), and ensure secure deployment of AI/ML models, including generative AI systems, across cloud environments (AWS, Google Cloud, Azure).</li><li>Implement AI/ML models in full-stack systems, ensuring robust backend processing and efficient front-end data visualization.</li><li>Engage with both internal and external stakeholders to continuously bring the latest advancements in generative AI, full-stack development, and AI/ML technologies to Pfizer, contributing to thought leadership through publications and presentations.</li></ul><p></p><p><b><b>ROLE RESPONSIBILITIES</b></b></p><ul><li>Partner with key therapy areas (e.g., Immunology &amp; Inflammation, Oncology, Internal Medicine) to identify scientific and technical challenges, define data pipelines, and implement full-stack solutions that leverage AI/ML methods, including generative AI models, to generate actionable insights and automate clinical trial documentation.</li><li>Translate complex clinical data and analytics requirements into full-stack digital products, ensuring that development priorities align with the overall clinical development goals.</li><li>Lead the end-to-end development of full-stack applications, from database schema design and API development to front-end user interfaces, ensuring seamless integration with AI/ML workflows and LLM-powered document generation systems.</li><li>Supervise and guide the deployment of robust back-end services that support predictive and classification algorithms, as well as generative AI models, ensuring scalability, security, and performance.</li><li>Develop and maintain dashboards and data visualization tools that provide clinical and operational teams with real-time analytics and insights driven by advanced ML models, while integrating tools for generating and reviewing AI-authored clinical trial documents.</li><li>Maintain an active external network in the AI/ML, generative AI, and full-stack development communities, continuously monitoring state-of-the-art capabilities and evaluating their potential impact on Pfizer’s development teams.</li></ul><p></p><p></p><p><b><b>QUALIFICATIONS</b></b></p><p><b><b>Basic Qualifications</b></b></p><ul><li>Bachelor’s degree in Computer Science, Software Engineering, Bioinformatics, Computational Biology, or a related technical discipline.</li><li>Minimum of 2 years of experience in full-stack development in the pharma, biotech, or tech industry.</li><li>Proficient in full-stack development, including back-end technologies (Node.js, Django, Flask) and front-end frameworks (React, Angular, Vue).</li><li>Strong understanding of database technologies (SQL, NoSQL) and experience in designing RESTful APIs and microservices architectures.</li><li>Experience with AI/ML model integration, including developing APIs to interface with ML models and building front-end components for real-time data visualization.</li><li>Experience working with large language models (LLMs) for generative AI applications.</li><li>Strong programming skills (Python, JavaScript, R) and familiarity with cloud technologies (AWS, Google Cloud, Azure).</li><li>Experience working with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure automation tools (Terraform, Ansible).</li><li>Strong written and verbal communication skills with the ability to translate complex technical concepts for non-technical stakeholders.</li></ul><p></p><p><b><b>Preferred Qualifications</b></b></p><ul><li>Master’s degree in a technical or scientific discipline (e.g., Computer Science, Computational Biology, Engineering).</li><li>Hands-on experience with the full-stack development of clinical trial management systems, focusing on integrating AI/ML-driven insights into clinical workflows, and automating document generation through LLMs.</li><li>Proven experience leading end-to-end clinical