We are looking for a technical intern to join the Data Science & Engineering (DSE) team, which is developing EntityRisk's core methodology and software. Our platform predicts the clinical, social, and commercial value of new medical technologies in the real world to help optimize risk-sharing, advance market access, improve evidence-generation investments, and correctly assess commercial value.
The role is for candidates pursuing a bachelor's or master's degree in a quantitative field such as statistics, economics, mathematics, engineering, finance, or computer science.
Interns work on data pipelines, perform initial and exploratory data analyses, aid in the implementation of statistical and machine learning algorithms, and help develop decision-analytic simulation models. They contribute to internal software libraries and help clients solve specific problems as part of consulting projects.
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. Candidates do not need to have experience with all the methods that we use but should be excited to learn about them. Applicants should be proficient in using a Python data and analytics stack.
Responsibilities
Aid in the parameterization and implementation of simulation models and advanced value assessment techniques to estimate the social value of medical technologies
Aid in the parameterization and implementation of microsimulation models to forecast the commercial value of new medicines and evaluate outcomes-based contracts
Collaborate with data engineers and data scientists to build data pipelines that take in a range of real-world (e.g., medical claims, electronic health records) or clinical trial data assets and create output in the form of analytic datasets
Maintain and contribute to a database summarizing the clinical efficacy of therapies across multiple salient disease areas
Program machine learning workflows and pipelines to predict health and financial outcomes distributions, estimate causal treatment effects, and quantify uncertainty
Contribute to internal software libraries by identifying bugs, suggesting new features, creating unit tests, writing documentation, and enforcing style conventions
Follow software best practices including version control (Git), code review, and continuous integration
Perform literature reviews related to therapeutic and disease areas of interest, regulatory and health authority guidelines, and innovative pricing
Present and communicate results to team members and clients
Qualifications
Enrolled in a BS or MS program in a quantitative field
Fluency in Python
Some experience writing technical documents (reports, manuscripts, presentations)
Seniority level
Internship
Employment type
Internship
Job function
Education and Training
Industries
Technology, Information and Internet
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