The Physiological Data Scientist will work as part of collaborative research teams to lead in the development and implementation of modern quantitative methods to extract insight from large clinical data sets. Strong understanding of methods of data analytics and statistical methodology required. Understanding of human physiology required. Success in this role will require a creative, engaged, flexible approach to research with a combination of strong technical and interpersonal skills.
1. Guide data collection, archival and curation for integration into databases with high data quality, transparency, validity and reliability. Coordinate and assist data review and cleaning reflecting appropriate physiological and engineering principles. Insure complete compliance with data security, privacy and governance standards while making data sets available to collaborators.
2. Perform exploratory data analysis and predictive modeling in pediatric biomedical research using machine learning, statistical, and mathematical analysis incorporating heterogeneous and complex data types under direct supervision.
3. Play a lead role in assessing and implementing computational, algorithmic, and predictive analytics approaches to understanding mechanisms, natural history, physiological signatures and effective treatments for pediatric disorders.
4. Guide the experimental design, execution, test and critical evaluation of methods as applied to translational data science research projects.
5. Contribute to design and conduct of continuous validation plans for production systems that incorporate models and algorithms, providing guidelines and support for large-scale implementation. Develop high-quality, readable, reusable code implementing models, algorithms and user-facing application programs.
6. Participate in communication of research methods, implementation, and results to varied audience of clinicians, scientists, analysts, and programmers. Lead manuscript writing for results publication, authors abstracts, and presents at professional conferences.
7. Other job functions as assigned.
1. MS required, PhD preferred in Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field. Alternately equivalent experience in data analysis and predictive modeling will be considered in lieu of relevant degree.
2. Minimum 5 year of experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects. Applications in biomedical/clinical research preferred.
3. Deep curiosity, experience and demonstrated ability acquiring new technical/analytic skills and domain knowledge to support successful contribution to research and development projects is required. Background knowledge of biomedicine, particularly physiology, is strongly preferred.
4. Extensive experience writing code in either applied educational or professional projects is required, using one or more of the following languages: Matlab, Python, Scala, Java or C++. Additional knowledge of statistical and machine learning tools preferred (such as R, SAS, ScikitLearn, etc.).
5. Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience. Strong research publication/presentation history preferred.
6. Experience creating informative visualizations for complex, high dimensional data required.
7. Experience with physiological signal processing or analysis of time series models required.