Research Data Engineer II

• Data science for Omics and Clinical Disease Progression Analytics
• Curate, harmonize, and integrate large-scale omics and clinical datasets to support disease progression research
• Develop and apply computational methods, algorithms, and predictive models to characterize and forecast disease trajectories
• Build custom data models and multi-omic integration pipelines to uncover biological mechanisms and clinical correlates of disease
• Design and implement processes, tools, and dashboards to monitor model performance, assess accuracy, and support reproducible research
• Data science in studies involving smart apps, wearable sensors, and new technologies
• Use statistics, machine learning, and computer science to analyze and interpret digital data and to compare to traditional assessments and scales
• Develop custom data models and algorithms to apply to data sets
• Use predictive modeling to analyze and characterize disease progression
• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• Develop processes and tools to monitor and analyze model performance and data accuracy
• Research & writing & publications related to data science modeling/analytics
• Disseminate research results through abstracts, publications, and other mechanisms
• Keep abreast of trends as they relate to the computer field by self-study, attending job-related seminars, courses, or conferences which enhance personal development
• Other duties as assigned

• Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or similar discipline Required
• 2 years of relevant experience Required
• or equivalent combination of education and experience Required
• Software Analytics, Machine and Deep Learning (e.g., (clustering, decision tree learning, artificial neural networks, etc.), Visual analytics, Natural Language Processing, Multimodal Data Fusion, Compressive Sensing, Data architectures
• Knowledge of advanced statistical techniques and concepts (e.g., regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
• Research & Project Management
• Coding knowledge and experience in computer languages (e.g., C, C++, Java, R, Python, SQL)
• Excellent communication skills for coordinating across teams
• A drive to learn and master new technologies and techniques

Master’s degree Preferred