Associate Director, Data Science & AI

CSLKing of Prussia, PA
Hybrid

About The Position

CSL is seeking a visionary and strategic leader to spearhead the development and commercialization of (Gen) AI solutions tailored for the life sciences industry. The Insights and Analytics team aims to enable improved decision making at CSL by leveraging superior data to identify actionable insights that drive enhanced performance. This role involves close collaboration with US & International business to empower smarter, data-driven decision-making. The Associate Director will spearhead the application of advanced analytics, machine learning, and AI solutions to unlock new insights, accelerate decision-making, and enhance commercial outcomes across CSL Behring’s portfolio. The focus will be on embedding AI and predictive modeling into core commercial processes, including patient identification, Medical and Tender Analytics, forecasting, and customer insights. This position serves as a bridge between CSL’s commercial business needs and technical innovation, ensuring scalable and responsible use of AI to create measurable business impact. The ideal candidate should possess deep domain expertise, a strong innovation mindset, and a proven track record of translating AI capabilities into impactful business solutions.

Requirements

  • Bachelor’s in data science, AI, Computer Science, Statistics, Applied Mathematics, or related quantitative discipline.
  • 10+ years of experience in advanced analytics, data science, or (Gen)AI within pharma/biotech or healthcare
  • Strong track record of developing and deploying machine learning models in commercial or clinical contexts.
  • Strong analytical and problem-solving skills, with the ability to interpret complex data and make informed decisions
  • Experience leading cross-functional AI/ML initiatives from concept through deployment.
  • Familiarity with cloud environments (AWS and Snowflake), data engineering workflows, and modern ML frameworks (TensorFlow, PyTorch, scikit-learn)
  • Familiarity with no-code data science SaaS tools
  • Ability to adapt strategies and approaches in a rapidly evolving technological landscape

Nice To Haves

  • Master’s degree preferred
  • Commercial analytics experience strongly preferred.
  • A deep understanding of the pharmaceutical industry, including regulatory requirements, market dynamics, and emerging AI technologies, with the foresight to identify and map both current and future AI opportunities, is preferred.
  • Experience in rare disease patient-finding models a plus.
  • Experience building evaluation frameworks for LLMs (factuality, faithfulness, bias, toxicity) and human-in-the-loop review
  • Knowledge of responsible AI frameworks, data governance, and compliance in pharma settings.
  • Experience Leading design, training/fine-tuning, and evaluation of ML/LLM/Agentic systems (retrieval-augmented generation, tool-use, routing, multi-agent workflows).

Responsibilities

  • Lead development and deployment of advanced analytics and AI models to address critical commercial challenges (patient identification in rare disease, HCP segmentation, Medical and Tender use cases)
  • In close partnership with ABCIA Commercial, Medical Affairs, and Market Access teams to ensure solutions are aligned with strategic business needs
  • Translate business problems into well-defined data science use cases and develop proof-of-concept pilots through to production
  • Drive adoption of AI-enabled tools across the commercial organization, ensuring business users understand and trust the outputs
  • Partner with I&T and Data Governance to ensure responsible AI practices, data quality, and scalable infrastructure
  • Drive CSL innovation in the field, leading to high visibility publications in top AI conferences and patents around Generative AI, reasoning, multi-agent systems, etc
  • Establish KPIs and frameworks to measure ROI and business impact of data science projects
  • Stay current with emerging AI/Machine Learning (ML)techniques, tools, and regulatory developments, and translate those into CSL’s context
  • Develop strong external partnerships (vendors and external partners) to bring cutting-edge AI capabilities into CSL and represent Commercial Data Science in cross-functional governance forums, ensuring alignment with global AI/ML initiatives
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