Research Associate Data Scientist - Omar Lab - Computational Biomedicine

Job Description

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

The Department of Computational Medicine (CBM) is a robust infrastructure established to develop, evaluate, and apply cutting-edge computational and statistical methods and software for the analysis of biomedical and clinical data across the Cedars-Sinai enterprise.

The Omar Lab is dedicated to developing robust AI‑powered tools to forecast the risk of adverse clinical outcomes in cancer patients at early stages. We use standard clinical data-primarily histopathology and radiology images-to build cost‑effective, accurate tools for personalized cancer risk assessment and management. Our research leverages the tumor microenvironment to extract high‑quality spatial and molecular features that guide our training process, guarding against overfitting. To learn more, please visit: Omar Lab | Cedars-Sinai.

Are you ready to be a part of breakthrough research?

The Research Associate Data Scientist participates in biomedical research projects using programming, data -mining, statistics, machine -learning, and visualization techniques to develop, evaluate, and/or apply algorithms and software for data analysis. Responsibilities include querying databases, data processing, supervised and unsupervised machine learning, deploying production models, and 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.

Primary Duties & Responsibilities:

• 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).
• Creates sustainable data science infrastructure and adheres to data analysis/machine learning best practices.
• Performs exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods.
• Works with senior or lead data scientists and principal investigators to identify areas where data science can best be applied to answer biomedical research questions.
• Keeps appropriate analytical records, documentation, and software version control.
• Performs all other duties as assigned.

Department-Specific Responsibilities:

• Participates in the development of innovative algorithms and analytical methods.
• Participates in the evaluation and interpretation of all analytical methods and results.
• Participates in the oral and written communication of scientific results including publications.
• Participates in analytical training activities for faculty, staff, and students.

Qualifications

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:

• Up to two (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 Python. College projects may be acceptable.
• Experience programming in R, Python, or Linux bash and genetics and genomics data analysis preferred.
• Experience in biomedical machine learning is preferred.
• Working knowledge of data privacy and security including best practices for data with personal health identifiers (PHI) covered under HIPAA.
• Strong interpersonal and communication skills. And has full command (verbal and written) of the English language.
• Demonstrates commitment to customer service and an ability to meet the needs and expectations of patients and health care colleagues.
• Demonstrated success working independently, forging relationships, and managing multiple tasks with minimal directions.
• Ability to promote and foster participation/collaboration among individuals and groups.
• Ability to handle multiple demands and/or manage complex and competing priorities.
• Ability to analyze qualitative and quantitative information for decision support.
• High level of proficiency using Microsoft Windows and other Microsoft Office software: MS Excel, Outlook, Powerpoint Word, etc.
• Must be able to manage competing priorities, while being extremely adaptable and flexible and maintaining a positive work environment.