Takeda is looking to transform pharmaceutical commercialization with advanced data science and AI by enhancing patient identification, HCP targeting, and omnichannel engagement through predictive modeling, machine learning, agentic AI, and generative AI technologies.
Requirements
- High level of proficiency in Artificial Intelligence, with demonstrated expertise in establishing GenAI (Generative AI) and Agentic AI methodologies and solutions.
- Strong technical expertise in machine learning, NLP, recommendation systems, and AI personalization use cases.
- Proficient in Data Science tools and languages such as Python, R, SQL, Databricks, and is familiar with cloud platforms (AWS, Azure, GCP).
- Experience with pharma data (e.g., IQVIA, Veeva, SP, claims, digital marketing) and strong understanding of compliance and privacy considerations.
- 10+ years of hands-on experience in AI/ML modeling, with at least 5 years in a pharmaceutical commercial analytics or healthcare setting required.
- Design and deploy predictive models—including logistic regression, ensemble methods, and other machine learning algorithms—for key applications such as trialist identification, patient segmentation, next-best-action (NBA), and HCP target prioritization.
- Create scalable, reusable frameworks for AI and machine learning experimentation and deployment across multiple therapeutic areas.
Responsibilities
- Advance Data Science and AI capabilities driving the utilization of predictive models in areas including Patient finding, HCP Targeting and Prioritization, Next Best Action Engines, predictive secondary data driven Patient and predictive Customer Segmentations.
- Advance Predictive Analytics for US. GI, NS, PDT, and Rare Disease Franchises, including new product launches or indications.
- Partner with BUs, BU Analytics & Insights, Marketing and Sales Ops, Data CoEs etc.to define use cases and integrate predictive model-driven decisioning into business decisions.
- Develop and execute a future-oriented data science strategy for commercialization, focusing on leveraging predictive and machine learning models to solve complex business challenges.
- Design and deploy predictive models—including logistic regression, ensemble methods, and other machine learning algorithms—for key applications such as trialist identification, patient segmentation, next-best-action (NBA), and HCP target prioritization.
- Lead the development of AI/ML algorithms to predict patient events, identify undiagnosed / misdiagnosed patients to drive targeted HCP engagements.
- Establish and lead GenAI and Agentic AI initiatives that are strategically aligned with CA&I goals.
Other
- Master’s or Ph.D. in Computer Science, Data Science, Statistics, Engineering, Economics or a related field required.
- 5+ years of prior management experience required.
- Expert in delivering persuasive presentations, conveying complex advanced Data Science driven insights to non-technical audience, and mentoring others in presentation skills
- Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams
- Strong project management skills, with the ability to manage multiple projects simultaneously
