Digital Health Data Strategy Lead

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Job Description

Role Summary

The Digital Health Data Strategy Lead will define, implement, and scale data strategies that enable Takeda’s Digital Health Products (DHPs) to generate high-quality, clinically meaningful, and regulatory-ready evidence. This role bridges science, technology, and strategy — combining data science expertise with strong leadership across medical, commercial, and R&D functions to ensure digital health data contributes directly to brand, asset, and evidence objectives.

Key Responsibilities

• Lead the development and execution of data strategies for Takeda’s Digital Health Products, ensuring alignment with brand, medical, and evidence plans.
• Translate clinical and scientific goals into actionable data requirements, architectures, and analytical roadmaps, enabling evidence generation and real-world data reuse.
• Apply advanced data science and statistical methodologies to structure, analyze, and interpret data from diverse digital health modalities (e.g., sensors, wearables, PPG, ECG, imaging, voice, activity, app usage).
• Partner cross-functionally with Medical Affairs, Market Access, R&D, and GEO to identify data opportunities that support integrated evidence plans (iEPs) and product value demonstration.
• Provide scientific and technical leadership to internal and external data teams (engineers, scientists, analysts, vendors), ensuring analytical rigor, reproducibility, and regulatory compliance.
• Contribute to scientific publications, conference presentations, and regulatory submissions, showcasing Takeda’s digital evidence leadership.
• Stay current on AI/ML, digital biomarker, and regulatory trends, advising on responsible data use, privacy, and ethical standards.

Requirements

• PhD or MSc in Data Science, Computer Science, Biomedical Engineering, Statistics, or a related quantitative field.
• 5+ years of experience applying data science in life sciences, healthcare, or digital health contexts, including RWD/RWE environments.
• Demonstrated expertise with machine learning, signal processing, or image analysis, and familiarity with sensor-derived or multimodal digital data.
• Proven ability to lead cross-functional scientific or technical projects, collaborating with Medical Affairs, Clinical, Market Access, and Regulatory functions.
• Strong background in statistical modeling, data interpretation, and experimental design; proficiency in Python and/or R.
• Experience with scientific publishing (peer-reviewed journals, conference presentations, or regulatory documentation).
• Excellent communication and leadership skills; capable of translating complex data concepts into strategic recommendations.
• Familiarity with GDPR, HIPAA, and ethical data governance in healthcare.

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