Clinical AI Automation Lead

You will be responsible for architecting and delivering Automation and AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. Working closely with business stakeholders, you will understand business requirements and design custom AI solutions to address complex challenges. This role offers the opportunity to accelerate AI adoption across the business landscape in the Statistical Applications and Data domain. Your key responsibilities include defining and leading AI use cases in clinical projects from start-up through close-out. This involves tasks such as protocol development, site management, and data review. To excel in this role, you must be a proficient programmer capable of developing AI solutions thoroughly. Additionally, you will be expected to coach and mentor junior AI/ML engineers to enhance and accelerate AI adoption in business processes. Required Technical Skills: - Bachelors degree in a relevant scientific discipline (e.g., Biomedical engineering, Life Sciences, Nursing, Pharmacy) or clinical background (e.g., MD- Doctor of Medicine OR RN - Registered Nurse) - Advanced degree (e.g., Masters or Ph.D.) in Data Science, AI/ML - Overall experience of 10-12 years with a minimum of 5-7 years in clinical research, particularly managing clinical trials in pharmaceutical, biotechnology, or contract research organization (CRO) settings - Minimum of 5-7 years of experience in AI research and development, specifically focusing on healthcare or life sciences applications - Strong understanding of clinical trial regulations and guidelines, including Good Clinical Practice (GCP), International Conference on Harmonization (ICH), and applicable local regulations - Proven track record in designing and delivering AI solutions, emphasizing foundation models, large language models, or similar technologies - Experience in natural language processing (NLP) and text analytics is highly desirable - Proficiency in programming languages such as Python, R, and experience with AI frameworks like TensorFlow, PyTorch, or Hugging Face - Knowledge of libraries such as SciKit Learn, Pandas, Matplotlib, etc. - Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and related services is a plus - Experience working with large datasets, performing data pre-processing, feature engineering, and model evaluation - Proficiency in solution architecture and design, translating business requirements into technical specifications, and developing scalable and robust AI solutions In summary, this role requires a seasoned professional with a strong background in AI, clinical research, and technical expertise to drive innovation and AI adoption in the pharmaceutical domain, particularly in clinical settings.,