• Lead Generative AI and LLM-driven projects • Design and optimize AI architectures for scalable production systems • Develop and deploy production-grade Python AI solutions • Implement Retrieval-Augmented Generation (RAG) pipelines • Mentor engineers and data scientists • Collaborate with engineering teams on cloud-native architectures • Ensure AI solutions are reliable, scalable, and maintainable

• Create advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources • Unearth data value by selecting and applying the right machine learning, deep learning and processing techniques • Refine data manipulation and retrieval through the design of efficient data structures and storage solutions • Innovate with tools designed for data processing and information retrieval • Dissect and document vast datasets, analyzing them to highlight patterns and insights • Solve complex challenges by developing impactful algorithms • Ensure model excellence by validating performance scores and analyzing Return on investment and benefits

• Create advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources • Unearth data value by selecting and applying the right machine learning, deep learning and processing techniques • Refine data manipulation and retrieval through the design of efficient data structures and storage solutions • Innovate with tools designed for data processing and information retrieval • Dissect and document vast datasets, analyzing them to highlight patterns and insights • Solve complex challenges by developing impactful algorithms • Ensure model excellence by validating performance scores and analyzing Return on investment and benefits • Articulate model processes and outcomes, documenting and presenting findings and performance metrics

• Lead end-to-end data management activities for clinical and/or consumer health studies • Oversee database build, CRF design, and data validation specifications • Ensure compliance with CDISC standards (SDTM) and regulatory requirements • Perform data cleaning, reconciliation, and query management to maintain data quality • Collaborate with cross-functional global teams (UK stakeholders, biostatistics, clinical, programming) • Manage external vendors/CROs and ensure timely delivery of milestones • Support interim analysis and database lock activities • Identify and resolve data discrepancies and quality issues • Contribute to process improvements and standardization initiatives