Principal AI and Automation Strategy Lead, Statistical Programming; Remote

Overview

Job Description The Principal, AI and Automation Strategy Lead will work with statistical programmers to understand data requirements and deliver state-of-the-art solutions leveraging machine learning models and artificial intelligence. The position is responsible for identifying opportunities within statistical programming workflows to enhance operational efficiency and partnering with leadership to prioritize them. Then they will gather requirements, and either build agents using enterprise low/no code solutions or partnering with Data, Technology, and Engineering (DTE) to develop and deploy more advanced AI solutions.

• Collaborate with statistical programming leadership and Data, Technology, and Engineering (DTE) teams to continuously identify areas for improvement in statistical programming, capture requirements, propose technically sound solutions to enhance efficiency and innovation, and implement, prioritize and confirm ongoing enhancements.
• Understand statistical programming workflows and processes: knowledge of daily responsibilities and tasks of statistical programmers, including data preparation, analysis, and reporting. Familiarity with industry standards (e.g., CDISC, SDTM, ADaM) and regulatory requirements to identify opportunities for process optimization and the effective integration of AI tools to enhance efficiency and productivity.
• Leverage a strong background in process excellence to identify inefficiencies, redesign workflows, and implement AI-driven solutions to optimize statistical programming processes.
• Strong knowledge of data engineering, AI/ML frameworks (e.g., PyTorch, Tensor Flow) and proficiency in programming languages such as Python, R, SAS, and SQL for data processing.
• Proficient in product and tool development with a strong grasp of UI/UX design principles to create intuitive and user-centric applications.
• Understanding of Machine learning Models, Neural networks, NLP (Natural Language Processing), and NLG (Natural Language Generation).
• Possesses expert knowledge of Small Language Models (SLMs), Large Language Models (LLMs), and LLM agents to enable intelligent automation and optimize statistical programming workflows.
• Experienced in working with FAISS and other vector databases, including tokenization strategies, and Retrieval-Augmented Generation (RAG) frameworks for efficient semantic search and contextualized AI responses.
• Knowledgeable about creation of no-code/low-code AI agents that automate tasks within statistical programming workflows, driving technological advancement, and enhancing departmental productivity.
• Understanding of LLMOps and MLOps to operationalize AI and machine learning models, ensuring scalability, reliability, and seamless integration into statistical programming workflows.
• Understanding of working in AWS cloud environment, including services such as Sage Maker, EC2, and S3 for scalable machine learning workflows.
• Work with DTE to design and execute comprehensive AI/ML model validation strategies, including data splitting, metric selection, cross-validation, robustness testing, fairness audits, and post-deployment monitoring.
• Experienced in providing training and technical support to end users for effective adoption and utilization of AI and automation solutions.
• Strong problem-solving and analytical abilities.
• Excellent communication skills for collaborating with stakeholders and bridging technical and domain teams.
• Experience working in fast-paced environment.
• Drives innovation within Statistical Programming by identifying and implementing new tools, technologies, and methodologies to enhance efficiency and effectiveness, while fostering collaboration with peers across relevant functional areas.
• Strong understanding of Generative AI ethics and governance frameworks: knowledge of ethical considerations, responsible AI practices, and governance frameworks related to the development, deployment, and use of Generative AI tools, including awareness of biases, data privacy concerns, transparency, accountability, and regulatory compliance.
• Shapes the technical strategy of the Statistical Programming group by…