Director, AI & Data Science

CSL Plasma•Waltham, PA

About The Position

The Director, AI & Data Science will shape and advance CSL Behring’s Commercial and Medical AI agenda within the Business Analytics, Reporting, Data & AI Strategy (BARDS) organization. The role leads strategy, development, governance, and deployment of advanced analytics, machine learning, generative AI, and AI-enabled decision support across Commercial, Medical, Market Access, and cross-functional priorities. It translates complex business needs into scalable solutions intended to improve decision-making, accelerate insight generation, support patient identification, optimize commercial execution, and deliver measurable business and patient impact. The Director serves as a senior thought partner to Commercial, Medical Affairs, Market Access, I&T, Data Governance, Legal, Compliance, Privacy, and external partners. Beyond developing and deploying AI/ML solutions, the role establishes the operating model, governance framework, adoption strategy, and capability roadmap for responsibly scaling AI and data science across the organization. It requires deep technical expertise, life sciences knowledge, cross-functional program leadership from concept through production, and the ability to influence senior stakeholders in a matrixed global environment. The role develops an AI and Data Science strategy and roadmap, prioritizes use cases, and leads solutions from problem framing and feasibility through pilot, production, adoption, and value measurement. Areas of focus include patient identification and rare disease diagnosis; Medical Analytics; tender and pricing analytics; forecasting and market insights; customer insights; competitive intelligence; and AI-enabled decision support. It sets responsible AI standards and controls, leads the strategic use and adoption of Dataiku and related platforms, builds internal capability through training and enablement, and partners across functions to embed AI into business processes. The Director also manages a portfolio of initiatives, vendors, and external partners; evaluates build-versus-buy options and emerging technologies; defines KPIs and ROI frameworks; and communicates the business value of AI and data science initiatives to senior and executive stakeholders. CSL Behring is a global biotherapeutics leader focused on therapies for patients in immunology, hematology, cardiovascular and metabolic, respiratory, and transplant therapeutic areas. CSL, the parent company, employs 32,000 people and delivers therapies in more than 100 countries.

Requirements

Bachelor’s degree in Data Science, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, Bioinformatics, Engineering, Epidemiology, Health Informatics, or a related quantitative discipline.
At least 12 years of experience in data science, advanced analytics, AI/ML, GenAI, commercial analytics, healthcare analytics, or life sciences analytics.
At least 5 years of experience leading cross-functional AI/ML or advanced analytics initiatives in pharma, biotech, healthcare, or a similarly regulated industry.
Demonstrated experience developing and deploying machine-learning models in commercial, medical, clinical, or healthcare contexts.
Experience translating business problems into data science use cases and moving solutions from concept to pilot to production.
Experience leading AI/ML or GenAI strategy, operating-model development, governance frameworks, and adoption planning.
Deep understanding of the pharmaceutical industry, including commercial models, medical affairs, market access, regulatory considerations, privacy, compliance, and data governance.
Strong understanding of responsible AI principles, including explainability, bias, fairness, factuality, human-in-the-loop review, data privacy, risk management, and auditability.
Experience with cloud environments and modern data science infrastructure, such as AWS, Snowflake, Databricks, or equivalent platforms.
Familiarity with machine-learning and AI frameworks such as Python, R, scikit-learn, TensorFlow, PyTorch, LLMs, retrieval-augmented generation, multi-agent workflows, and GenAI evaluation frameworks.
Ability to influence senior stakeholders, lead through ambiguity, and drive alignment across matrixed global teams.
Demonstrated ability to manage vendors, external partners, and cross-functional delivery teams.
Strong executive communication skills and ability to translate complex technical topics into business implications and recommendations.

Nice To Haves

Master’s degree or Ph.D.
Experience with rare-disease patient identification, patient-finding models, HCP segmentation, care-gap analytics, forecasting, Medical Analytics, Tender Analytics, or customer insights.
Experience with Dataiku or similar enterprise AI/ML platforms.
Experience building or scaling AI/data science capabilities within a Commercial, Medical, or Market Access organization.
Experience designing AI governance models and working with Legal, Compliance, Privacy, I&T, and Data Governance teams.
Experience leading teams or indirect resources across internal employees, contractors, vendors, and business stakeholders.
Experience with GenAI solutions for insight generation, competitive intelligence, forecasting, content analysis, decision support, or workflow automation.
Experience with patient-identification and rare-disease diagnosis use cases using claims, EMR, lab, specialty pharmacy, CRM, and other real-world data sources.
Experience developing ROI models, adoption metrics, and business-impact frameworks for data science and AI programs.
Strong publication, patent, conference, or thought-leadership experience in AI, machine learning, data science, healthcare analytics, or life sciences innovation.

Responsibilities

Develop and lead the BARDS AI and Data Science strategy aligned with CSL Behring’s Commercial, Medical, Market Access, and enterprise priorities.
Build and maintain an AI/DS roadmap, prioritizing high-value use cases across patient identification, rare disease diagnosis, Medical Analytics, Tender Analytics, forecasting, customer insights, competitive intelligence, and decision support.
Partner with senior business leaders to identify challenges where AI, machine learning, GenAI, and advanced analytics can create measurable value.
Establish an AI use-case intake and prioritization framework that considers value, feasibility, data readiness, risk, effort, governance, and ROI.
Translate emerging AI trends, technologies, and regulatory considerations into practical strategies for Commercial and Medical applications.
Lead development and deployment of advanced analytics, predictive modeling, machine learning, GenAI, and agentic AI solutions.
Oversee AI/ML use cases from problem framing and feasibility through proof of concept, pilot, production deployment, adoption, and value measurement.
Provide technical and strategic leadership for patient-identification and rare-disease patient-finding models, including PID/SID, HAE, and other therapeutic areas.
Lead AI-enabled Medical Analytics capabilities, including care-gap identification, medical-impact measurement, KOL and HCP insights, evidence-generation support, field-medical effectiveness, and disease-education opportunities.
Partner with Tender and Pricing teams on analytics for tender performance, price erosion, market dynamics, competitive behavior, and decision support.
Enable GenAI and machine-learning solutions for forecasting and market insights, including analog identification, scenario planning, signal detection, and insight generation.
Partner with I&T, Data Governance, Legal, Compliance, Privacy, Medical, and Commercial stakeholders to support responsible and compliant AI development and deployment.
Establish AI/ML and GenAI governance standards for validation, explainability, human-in-the-loop review, bias assessment, factuality, faithfulness, auditability, data quality, privacy, and risk management.
Ensure AI-enabled tools have appropriate controls, documentation, monitoring, user training, and business ownership; represent BARDS in relevant AI and governance forums.
Develop practical frameworks that balance innovation with appropriate guardrails in a regulated life sciences environment.
Lead strategic use and adoption of Dataiku and related AI/ML platforms, defining operating processes for intake, prioritization, governance, enablement, value tracking, and deployment.
Partner with business users, data scientists, analysts, and I&T teams to improve adoption of AI-enabled workflows and self-service analytics.
Build internal AI and data science capability through training, coaching, best-practice sharing, reusable frameworks, and hands-on enablement.
Serve as a strategic bridge between business needs and technical execution across Commercial, Medical Affairs, Market Access, I&T, Data Governance, and external partners.
Lead cross-functional working teams to define requirements, align success measures, resolve dependencies, and implement priority AI/ML initiatives.
Influence across a matrixed organization and support change management and adoption planning so users understand, trust, and act on AI-generated insights.
Lead a portfolio of AI and data science initiatives, ensuring prioritization, resourcing, governance, delivery milestones, and value tracking.
Manage external vendors and partners; evaluate build-versus-buy options and recommend vendors, platforms, partnerships, and emerging technologies.
Ensure vendor solutions align with CSL’s data architecture, governance expectations, responsible AI principles, and business objectives.
Represent CSL Commercial Data Science in external forums, vendor discussions, and cross-functional governance meetings.
Define KPIs and ROI frameworks and ensure prioritized use cases have clear objectives, success measures, business ownership, adoption plans, and measurable outcomes.
Track and communicate value, including patient-identification improvements, faster insight generation, better decisions, efficiency gains, reduced reliance on external consulting, improved field execution, and stronger Medical and Commercial impact.
Translate technical outcomes into clear business narratives for senior and executive stakeholders.