Join us as we translate today's discoveries into tomorrow's medicine!

Dr. Nicholas Tatonetti is Vice Chair of Operations in the Department of Computational Biomedicine and Associate Director of Computational Oncology in the Cancer Center at Cedars-Sinai Medical Center. His lab at Cedars-Sinai is focused on using massive-scale real clinical and molecular data for making robust and validated scientific discoveries, with a particular focus on detecting, explaining, and validating drug effects and drug interactions. Dr. Tatonetti has published over 180 peer-reviewed scientific publications across medicine, systems biology, machine learning, and bioinformatics. To learn more, visit TLab – Data-Driven Drug Safety (tatonettilab.org).

Are you ready to be a part of breakthrough research?

The Research Senior Data Scientist participates in biomedical research projects using programming, data mining, statistics, machine learning, and visualization techniques to invent new algorithms, methods, and software for data analysis. Responsibilities include querying databases, data cleaning and quality control, supervised and unsupervised machine learning, parametric and nonparametric statistical methods, deploying production models, and leading the communication of scientific findings via peer-reviewed publications and scientific conferences. Writes clean, performant, reusable code managed on GitHub to perform repeatable analyses and to train and deploy models to multiple environments. Serves as a resource 1-2 staff to assist with the development, evaluation, and/or application of algorithms, methods, and software for data analysis.

Primary Duties & Responsibilities:

• Invents, develops, evaluates, and applies computational and statistical methods including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data.
• Creates database-to-deployment pipelines for models using necessary programming languages (primarily R, Python, SQL, neo4j).
• Creates sustainable data science infrastructure and adheres to data analysis standard methodologies.
• Leads with the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications.
• Performs data cleaning, quality control, and analytical methods.
• Performs exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods.
• Leads discussions with 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 GitHub.
• Provides feedback to the lead for appraisals relating to research projects and work performance.

Education:

• Bachelor's degree in Computer Sciences, Machine Learning, Applied Mathematics, Econometrics, Statistics, Engineering, Physics, or related field, required.
• Master's degree, preferred.

Experience and Skills:

• Minimum of 5 years of professional experience in data science, healthcare, or pharmaceutical industries or universities working with biomedical, clinical, or biological data.
• Experience programming at an intermediate or advanced skill level with a high-level programming language such as R or Python.
• Experience programming at an intermediate proficiency level in SQL.
• Experience with the development and evaluation of computational and/or statistical methods including machine learning for data analysis.
• Work experience should include being an author or co-author on one or more peer-reviewed scientific papers published in journals.