What You’ll Learn:

✔ How two leading statisticians transitioned into data science

✔ The key differences (and overlaps) between data science, statistics, big data, and machine learning

✔ Why data science is more than hype—and why statisticians are needed more than ever

✔ The role of visualization and statistical learning in interpreting high-dimensional biomedical data

✔ Real-world applications of data science in biomarker discovery, precision medicine, and pharmacovigilance

✔ What makes data science in pharma different from tech giants like Google or Amazon

✔ Tips for statisticians who want to get started in data science

Why You Should Listen:

If you're a statistician wondering whether data science is your next career step—or simply curious about how the two fields intersect—this episode offers an honest, expert-led exploration. Yannis and Rajat pull back the curtain on what data science really involves, how it's transforming pharma and healthcare, and what skills and mindset statisticians can bring to this evolving space.

Links:

🔗 Explore Cytel’s data science insights and case studies

🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician.

🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills.

🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine.

🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities.

If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss.

Join the Conversation:
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