Health Economics & Modeling Intern

About The Role

We are seeking a dedicated PhD student with a background in health economics and/or simulation modeling to join the Data Science & Engineering (DSE) team at EntityRisk for a full-time, paid internship lasting 12 to 14 weeks. The DSE team develops Python-based simulation modeling and decision analysis software to address challenges faced by biopharmaceutical clients.

As a PhD intern, you will have the opportunity to implement sophisticated health economic models that assess the cost-effectiveness of medical technologies. You will receive mentorship from a multidisciplinary team, gaining valuable insights and hands-on industry experience solving real-world problems within the pharmaceutical industry. Your internship will kick off with a 4- to 6-week training period focused on software engineering best practices, including version control, coding style, collaboration, automation, reproducibility, and testing. You will then apply your newly acquired skills to a client project where you will:
• Conceptualize a cohort or microsimulation model
• Program the model using Python
• Utilize advanced techniques such as generalized risk-adjusted cost-effectiveness (GRACE)
• Write automated tests to ensure the internal validation of your model
• Produce reproducible results presented through an interactive report or web application
• Present your findings to team members and/or clients

All tasks will be performed in close collaboration with DSE team members to enhance your development experience. You will participate in code review and receive constructive feedback.

Ideal candidates are collaborative and intellectually curious with a desire to expand their skills and knowledge. Successful candidates will have good written and verbal communication skills in addition to strong technical skills.

Responsibilities
• Create a technical report that describes your health economic methods
• Design and develop a Python package for effective implementation of your model
• Implement computationally efficient algorithms
• Adopt reproducible workflows to ensure consistent and reliable results
• Follow software best practices including version control (Git), code review, continuous integration, and continuous deployment
• Present and communicate results to team members and clients using slide decks, web apps, and/or effective written/oral communication

Qualifications
• Currently enrolled in a PhD in Health Economics, Decision Science, or a related quantitative field
• Experience with at least one of Python or R
• Experience programming simulation models
• Knowledge of cost-effectiveness analysis methods
• Experience writing technical documents (reports, manuscripts, presentations)

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