Grow your career at Cedars-Sinai!

Data is vital to advance clinical knowledge across a spectrum of medical and surgical fields. Are you ready to transform data discoveries into valuable information, which will empower tomorrow's medicine?

Dr. Pramod Butte, Ph.D. is looking for a Research Associate Data Scientist to join a diverse team!

The primary focus of the Butte Laboratory is translational research in the field of bio-photonics. The Butte Lab is developing novel intra-operative imaging/visualization technologies to aid surgeons in achieving near-complete tumor excision. To learn more about the Butte Lab, please visit this website.

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 nonparametric 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 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 Python, R, C ).
• Creates sustainable data science infrastructure and adheres to data analysis/machine learning standard processes.
• Performs exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods.
• Works with senior or lead data scientists, research programmers, and principal investigators to identify areas where data science can best be applied to answer biomedical research questions.
• Tests and validates code to ensure adaptability of data applications.
• Performs all other duties as assigned.

Department-Specific Information:

• Possess deep and broad experience in Signal-to-Noise (SNR) analysis, Digital Signal Processing (DSP) and Image Processing to advance and improve the imaging capability of the Time-Resolved Fluorescence Spectroscopy system (TRFS) for surgical cancer applications.
• Proficient in computational modeling and simulation of multi-dimensional data in Python (numpy, scikit, etc)
• Develops new algorithms to improve signal and image filtering, including various forms of filters
• Proficient in analyzing forms of noise, determining Signal-to-Noise Ratio (SNR)
• Conceives and proposes design improvements, development advancements, and maintenance enhancements of the product
• Possess detailed understanding of in-house developed imaging technology, its product implementation, and its application in medicine.
• Recommends possible experimental avenues of investigation to aid in increasing system signal, noise, and imaging performance.
• Supports transfer of algorithms, technology, and results to third party contract manufacturers and regulatory personnel
• Analyzes data and implement programs for data analysis as needed.
• Understands the details and rationale behind medical standard of care workflow
• Follows IRB protocols and clinical trial procedures.
• Helps and participates in collection of clinical data on an as-needed basis.

Education:

• Bachelor's degree in Computer Science, Machine Learning, Applied Mathematics, Biomedical Imaging, Statistics, Engineering, Physics, or related field, required.
• Master's degree in these fields is preferred.

Experience and Skills:

• 0-2 years of professional experience in the 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.
• Experience programming at a basic to intermediate proficiency level in SQL.
• Experience in healthcare machine learning is preferred.