Data Intelligence Intern

Join a Legacy of Innovation 125 Years and Counting!

Daiichi Sankyo Group is dedicated to the creation and supply of innovative pharmaceutical therapies to improve standards of care and address diversified, unmet medical needs of people globally by leveraging our world-class science and technology. With more than 125 years of scientific expertise and a presence in more than 20 countries, Daiichi Sankyo and its 18,000 employees around the world draw upon a rich legacy of innovation and a robust pipeline of promising new medicines to help people. In addition to a strong portfolio of medicines for cardiovascular diseases, under the Group’s 2025 Vision to become a “Global Pharma Innovator with Competitive Advantage in Oncology,” Daiichi Sankyo is primarily focused on providing novel therapies in oncology, as well as other research areas centered around rare diseases and immune disorders.  

We are currently seeking a Data Intelligence Intern for Summer 2026. This full-time position works for approximately 37.5 hours per week.

Responsibilities:

The successful candidate will support an applied research initiative focused on developing standardized benchmarks for evaluating multimodal AI models in real-world evidence (RWE) research. This project centers on constructing synthetic patient cohorts that provide a reproducible, transparent testing environment for predictive models. These synthetic cohorts enable rigorous stress-testing under varying population characteristics, disease prevalence, and treatment practices. Benchmarking will emphasize clinically meaningful outcomes such as mortality, length of stay, and adverse events—offering a systematic foundation for assessing model performance, robustness, and generalizability. Ultimately, this work aims to establish a scalable framework for developing trustworthy AI systems that advance the use of real-world evidence in drug development and healthcare decision-making.

In addition to this research project, the intern will contribute to other ongoing business and data science initiatives involving data analysis, model development, and report generation.

Key Responsibilities:

Data Analysis

• Apply data science and statistical techniques to analyze complex data sets relevant to ongoing research and business projects.
• Support the design, implementation, and maintenance of analysis pipelines and data tools.
• Prepare clear, well-structured reports, visualizations, and presentations that summarize analytical findings.

Statistical Programming

• Use programming languages such as Python and R to perform data wrangling, statistical modeling, and automated report generation.
• Assist in developing and validating AI/ML models for predictive or benchmarking purposes.

Team Collaboration

• Collaborate closely with senior data scientists, statisticians, and project stakeholders to ensure analytical rigor and reproducibility.
• Contribute to internal discussions, project documentation, and knowledge-sharing sessions.

Professional Development

• Engage in learning opportunities such as seminars, workshops, and mentorship sessions.
• Proactively build expertise in data science, statistical methodologies, and relevant software tools used in healthcare analytics.
 

This internship offers a hands-on opportunity to work at the intersection of AI, data science, and real-world evidence, contributing to initiatives that have direct implications for drug development and clinical research. The role is ideal for candidates who are curious, detail-oriented, and eager to apply quantitative skills to impactful problems in healthcare innovation.
  
Qualifications:

• Enrollment in a graduate-level program in Data Science, Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
• Excellent communication skills, both written and verbal.
• Ability to work effectively in a collaborative team environment.
• Strong analytical and problem-solving skills.
• Enthusiasm for learning and a strong interest in AI, machine learning, programming, and data analysis.
• Proficiency in Python (preferred) or R.
• Good knowledge of commonly used statistical methodology (e.g., regression modeling)
• Familiarity with machine learning algorithms (Random Forest, Neural Nets, XGBoost, etc.) and concepts (nested cross-validation, Explainable AI, etc.)
• Strong attention to detail and the ability to manage and organize data.
• Compliant with internal and external compliance practices to ensure the integrity of work.

Daiichi Sankyo, Inc. is an equal opportunity/affirmative action employer.  All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.