Research Associate Data Scientist

Cedars-Sinai Medical Center • Los Angeles, CA

1d • Onsite

About The Position

This position involves assisting with the development, evaluation, and application of computational and statistical methods, including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data. The role also includes presenting and communicating scientific results through various channels and creating database-to-deployment pipelines for models. The Research Associate Data Scientist will contribute to building sustainable data science infrastructure, adhering to best practices, and performing exploratory data analysis. Collaboration with senior data scientists and principal investigators is key to identifying areas where data science can address biomedical research questions. Testing and validating code for robustness is also a core responsibility.

Requirements

• Master’s degree or foreign equivalent in Electrical Engineering, Computer Science, Machine Learning, Applied Mathematics, Biomedical Imaging, or related field
• Three (3) years of experience as a Research Associate Data Scientist, Computer Engineer, Biomedical Data Scientist, or related occupation
• Experience with Python, C++, and R
• Experience developing, testing, validating, and optimizing production-level, version-controlled code (GitHub/GitLab and Azure DevOps) for algorithm development, statistical analysis, and deployment
• Experience implementing supervised and unsupervised learning algorithms (random forests, support vector machines, clustering, deep learning)
• Hands-on expertise training, fine-tuning, and deploying deep learning models using frameworks (PyTorch and TensorFlow)
• Experience adapting machine learning methods to biomedical research problems
• Experience building end-to-end database-to-deployment pipelines including querying large relational databases (SQL), data cleaning, model training, validation, and deploying models in multiple computing environments
• Experience communicating scientific results effectively through peer-reviewed publications, patents, conference presentations, and internal technical reports
• Experience working with medical imaging data, including familiarity with industry-standard imaging formats (DICOM), image preprocessing workflows (segmentation, denoising, registration, resampling, and normalization), and use of imaging software libraries (SimpleITK, MONAI, or NiBabel) to prepare data for machine learning analysis
• Experience managing, processing, and optimizing large-scale 3D and 4D time-series datasets for deep learning model development on High-Performance Computing (HPC) or cloud-based GPU clusters

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, 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 GitHub.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level