Role Summary
Associate Director, AI Innovation at BeOne Medicines. Drive the integration and enablement of AI-driven platforms using Retrieval-Augmented Generation (RAG) models and agentic AI to synthesize large datasets into actionable insights, supporting decision-making across Commercial, Medical, and cross-functional teams in the US, EU, and Canada.
Responsibilities
- Lead the integration, enablement, and innovation of AI-driven platforms, incorporating RAG models and agentic AI to automate data synthesis and insight generation.
- Develop and implement Retrieval-Augmented Generation (RAG) pipelines for real-time, context-aware decision support.
- Leverage agentic AI approaches to build autonomous AI agents that optimize data-driven recommendations and adapt to changing business needs.
- Apply advanced AI techniques to transform structured and unstructured data into business-critical insights.
- Develop AI-driven decision-support tools to optimize commercial strategy and enhance medical engagement.
- Collaborate cross-functionally with Commercial, Medical, and other stakeholders to identify AI opportunities and deploy solutions.
- Evaluate and refine AI models for improved accuracy, efficiency, and business impact in decision-making processes.
- Design and implement scalable AI-driven analytics frameworks for real-time data interpretation and scenario modeling.
- Conduct hypothesis-driven exploratory analyses using deep learning, NLP, and generative AI to uncover actionable insights.
- Stay at the forefront of AI innovation and evaluate new methodologies, tools, and platforms.
- Present insights and AI-driven recommendations to senior leadership with strategic alignment and impact.
Education
- Master's or PhD in AI, Data Science, Computer Science, Engineering, Statistics, or related field.
Qualifications
- PhD with 8+ years or Master's with 10+ years of experience in AI-driven analytics, machine learning, or data science.
- 8+ years of consulting or commercial pharmaceutical industry experience.
- Hands-on experience with Retrieval-Augmented Generation (RAG) models and integrating AI with enterprise knowledge bases.
- Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) for similarity search and knowledge retrieval.
- Deep understanding of agentic AI approaches and autonomous AI agents.
- Expertise in NLP, deep learning, and machine learning for AI-based insights.
- Advanced knowledge of ML algorithms (classification, regression, clustering, reinforcement learning, anomaly detection).
- Experience with big data environments (Hadoop, Spark) and AI tools (Snowflake, Databricks, LangChain).
- Proficiency in Python, SQL, and cloud-based AI services (AWS, Azure, or GCP).
- Strong grasp of statistical methodologies including Bayesian inference, A/B testing, and causal inference.
Skills
- Ability to translate AI insights into clear, strategic recommendations for business leaders.
- Influencing skills and collaboration with cross-functional teams.
- Experience leading AI/analytics initiatives with measurable business impact.
- Excellent communication and storytelling to convey AI-driven insights to executives.
Travel