Research Associate Data Scientist -Computational Biomedicine

Job Description

The Research Associate Data Scientist participates in biomedical research projects using programming, data-mining, statistics, machine learning, and visualization techniques to assist with the development, evaluation, and/or applications of algorithms, methods, and software for data analysis. Responsibilities include querying databases, data cleaning and quality control, supervised and unsupervised machine learning, parametric and non-parametric statistical methods, deploying production models, and assisting with the communication of scientific findings via peer-reviewed publications and scientific conferences.

Writes clean, performant, reusable code managed on Git Hub to perform repeatable analyses and to train and deploy models to multiple environments.

• Assists with the development, evaluation, and/or application of computational and statistical methods including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data.
• Assists with the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications.
• Creates database-to-deployment pipelines for models using the necessary programming languages (primarily R, Python, SQL, neo4j).
• Creates sustainable data science infrastructure and adheres to data analysis/machine learning best practices.
• Performs data cleaning, quality control, and exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods.
• Assists research, senior research, and/or lead research data scientists and principal investigators to identify areas where data science can best be applied to answer biomedical research questions.
• Tests and validates code to ensure robustness of data applications with version control through Git Hub.

• Education: Bachelor’s degree in computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline required.
• Masters in the Sciences computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline is preferred.
• 0 to 2 years of professional experience in healthcare or pharmaceutical industries working with biomedical data.
• Experience programming at an intermediate skill level with a high-level programming language such as R or Python. College projects may be acceptable.
• Experience programming at a basic to intermediate proficiency level in SQL.
• Experience in biomedical machine learning is preferred.