Cedars-Sinai Research Associate Data Scientist - Computational Biomedicine in Los Angeles, California
When the work you do every single day has a crucial impact on the lives of others, every effort, every detail, and every second matters. This shared culture of happiness, passion, and dedication pulses through Cedars-Sinai, and it’s just one of the many reasons why we rank as one of the top hospitals in the nation by U.S. News & World Report.
Are you ready to be a part of breakthrough research?
The Department of Computational Medicine is a robust infrastructure that supports bioinformatics, computational, and statistical needs of all faculty across the Cedars-Sinai enterprise and the expanding needs of our Departments and Institutes.
The Research Associate Data Scientist delivers analytical solutions using programming, data-mining, statistics, machine-learning and visualization techniques. Responsibilities include querying databases, data processing, supervised and unsupervised machine learning, deploying production models, and communicating findings. Writes clean, performant, reusable code to perform repeatable analyses and to train and deploy models to multiple environments.
Primary Duties & Responsibilities:
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 business partners to identify areas where data science can best deliver value.
Tests and validates code to ensure the robustness of data applications.
Performs all other duties as assigned.
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 communication of scientific results including publications.
Participates in analytical training activities for faculty, staff, and students.
- Bachelor's degree in Computer Sciences, Machine Learning, Applied Mathematics, Econometrics, Statistics, Engineering, Physics, or related field, required. Master's degree, preferred.
Experience and Skillset:
Up to two (2) years of professional experience in healthcare or pharmaceutical industries working with electronic medical record 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.
Collaborates to problem solve and make decisions to achieve desired outcomes.
Establishes effective working relationships with cross-functional team(s).
Cultivates and maintains strong customer relationships and rapport with stakeholders and/or client groups.
Working knowledge of The Joint Commission and other state and local regulatory requirements.
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.
Cedars-Sinai is an EEO employer. Cedars-Sinai does not unlawfully discriminate on the basis of the race, religion, color, national origin, citizenship, ancestry, physical or mental disability, legally protected medical condition (cancer-related or genetic characteristics or any genetic information), marital status, sex, gender, sexual orientation, gender identity, gender expression, pregnancy, age (40 or older), military and/or veteran status or any other basis protected by federal or state law.