Senior Data Scientist, Epidemiology
Our client is a targeted precision medicine company for cardiovascular disease. Their mission is to improve access and outcomes for people with heart conditions.
What you will do
- You will be a hands-on individual contributor using your skills in clinical data analysis to implement study protocols and publish your analyses in high-impact clinical journals as the first author.
- You will use your constantly growing expertise in working with big messy data (e.g. electronic health records, claims, etc.) to create cohorts of eligible populations.
- You will use your skills in R and/or Python and your dedication to open and reproducible science to develop libraries that we can use to easily describe, predict, and estimate clinical effects of interest.
- You will contribute to rigorous and reproducible scientific publications
- MD, or PhD in Data Science, Epidemiology, Public Health, Computational Biology, or related field.
- 5+ years of experience in: epidemiology, biostatistics, health economics, applied statistics, or related field.
- At least one first author publication, or previously led a similarly complex project from start to finish.
- Hands-on experience in at least one project using large healthcare data, such as claims or electronic health records.
- Completed at least one complex project using R or Python and relevant data science libraries (e.g. tidyverse, sklearn, etc.).
- Familiar with best coding practice, including functional programming, style guides, version control, and appropriate levels of documentation.
- Experience implementing and interpreting statistical inference and modelling methods within Bayesian paradigms (e.g. t-test, Cox regression, etc.).
- You can use and interpret epidemiologic concepts (e.g. study design, odds ratios, etc.) and can differentiate between statistical and clinical significance.
- You have published 1+ clinical research articles as the first author.
- You have experience with 1+ of SQL, Julia, Docker, Git.
- You have experience in time series analyses and/or signal processing.
- You are excited about transparency, rigor and reproducibility in biomedicine.
- You can articulate technical concepts to a non-technical audience