Principal Analyst — Data Science

Design, execute, and interpret advanced statistical analyses — segmentation, trend and longitudinal analysis, behavioral modeling, signal detection, and inference — to explore complex questions across large, complex datasets.

Apply statistical and machine-learning methods (e.g., regression and mixed-effect models, time-to-event analysis, Bayesian methods, clustering, and variable-selection approaches) to generate fit-for-purpose evidence that informs Medical strategy.

Navigate ambiguity and frame the right questions, establishing and enforcing standards for methodological rigor, validation, and reproducibility, and clearly communicating assumptions, limitations, and confidence in results to technical and non-technical audiences.

Design and build agentic-AI and GenAI-augmented workflows with human-in-the-loop (HITL) oversight — orchestrating specialized AI agents (e.g., via Claude Code and modern LLM frameworks) to accelerate analysis, data preparation, and insight generation at scale.

Prototype, evaluate, and operationalize AI/ML and agentic use cases responsibly, defining guardrails, evaluation metrics, and validation practices appropriate for a regulated (GxP) environment.

Perform ETL and develop/orchestrate reproducible data and model pipelines using SQL, Python, and R, partnering with DD&T and data platform teams to ensure data structures enable modeling and automation.

Skilled at data storytelling — translate model outputs and AI-generated findings into compelling narratives, visualizations, and recommendations tailored to different audiences, from senior leadership to field teams.

Anticipate business needs and act as a strategic thought partner to therapeutic-area and functional leads — helping frame questions, define success measures, and guide data-informed decisions on engagement effectiveness, content impact, and HCP behaviors.

Lead prioritization and scoping of statistical and AI work within the GCC, balancing quick-turn deliverables with deeper strategic and experimental projects, and drive analytical and AI literacy across US Medical stakeholders.

Mentor Analysts and Senior Analysts across the GCC on statistical methods, machine learning, and applied AI, and contribute to team knowledge management (methodological standards, reusable model components, and evaluation frameworks).

Bachelor's Degree required in a quantitative field (e.g., Statistics, Biostatistics, Data Science, Computer Science, Economics, or a related discipline); advanced degree (MS/PhD) in Statistics, Data Science, or a related field strongly preferred.

5–6 years of progressive quantitative experience in data science, statistics, or advanced analytics — ideally within Medical Affairs, Commercial, or similar data-rich functions in pharmaceutical or life sciences — with a significant portion focused on statistical modeling and applied machine learning.

Strong programming skills in Python and R, and strong proficiency in SQL for deep analysis, are required; hands-on experience building and validating statistical and machine-learning models is required.

Demonstrated experience with GenAI and agentic-AI approaches — including human-in-the-loop (HITL) multi-agent workflows and tools such as Claude Code — to surface insights and automate analysis at scale is strongly preferred.

Familiarity with pharmaceutical data ecosystems (CRM, engagement platforms, MyMedInfo, content systems) and comfort working within modern data platforms (e.g., Databricks) in partnership with DD&T.

Working knowledge of Tableau for communicating model results, and experience operating in a regulated (GxP) environment, are preferred.

Experience in a GCC, captive, or offshore delivery model supporting global or US-based stakeholders, with willingness to maintain overlap hours with US time zones, is strongly preferred.

Takeda is leading a digital revolution. We’re not just transforming our company; we’re improving the lives of millions of patients who rely on our medicines every day.

As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization.

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