Research Computational Scientist II

CHOC • Orange, CA

1d

About The Position

The Research Computational Scientists (RCS) II will collaborate with providers, researchers, and other associates to provide computational services required for research and implementation of research findings. This requires a multidisciplinary training in the computational and data sciences including statistics, computer science, and artificial intelligence. The role will support the development and innovative application of advanced simulation, data analyses, visual analytics, or other computational techniques to research problems across the CHOC Health System. Daily tasks include working closely with providers, researchers, and other associates to develop or deploy computational solutions required for improving knowledge, the health of patients, and the financial health of the organization. These computational solutions will include development of new statistical, machine-learning, and artificial intelligence algorithms, improvement of existing algorithms, and analyses of data from the electronic medical records of patients. Data sources will span not just the electronic medical records but other sources of data relevant to research and organizational growth. The goal is the development of deeper understanding, insight, and prediction of events that may foster the health of children and the health of the care system as well.

Requirements

• Minimum two years of related work experience.
• Experience should include the application of advanced statistical algorithms and computational and data science methods in the analyses of medical data including generalized linear models across a wide range of statistical distributions, time series analyses, and longitudinal data analyses.
• Experience with SQL programming and data preprocessing for research studies are also required.
• Previous participation in research during academic training, internships, or prior job experience that resulted in one or more peer-reviewed publications is required.
• Master of Science in the computational and data sciences including statistics, artificial intelligence, biostatistics, bioinformatics, and statistical genetics.
• Previous (paid or unpaid) work within a research group in college or other institutions.
• Expected to be comfortable with the wide range of statistical learning algorithms and development of simulations for empirical statistical analyses using a statistical programming language or C/C++.
• At least 5 of the following: R Statistical Programming Language, SPSS, SAS, Python, C/C++, and SQL, TensorFlow, Keras, PyTorch, and Apache Spark and Hive.

Nice To Haves

• Prior peer-reviewed publications in PubMed-indexed journals include first or last authorship.
• Familiarity with Machine-learning, Artificial Intelligence, Casual Inference or Bayesian Statistics is also required through prior coursework, publications, or informal studies of these methods.
• Previous experience with high-level programming languages such as SAS, R Statistical Programming Language, SPSS, C/C++, Python, and TensorFlow, Keras or PyTorch for time series and other sequence data prediction.
• Doctoral degree in the computational and data sciences including artificial intelligence, statistics, biostatistics, bioinformatics, and statistical genetics.

What This Job Offers

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