We are seeking a Data Science Fellow, to develop essential skills in healthcare analytics and modern methods in artificial intelligence/machine learning to advance research in precision medicine. The data science fellow will collaborate closely with American Heart Association scientists, clinical and research volunteers, and program managers to drive innovation and solve medical research challenges. Responsibilities - Develop and execute data science projects in health care, which focused on clinical data, equity and disparity in clinical outcomes and prediction algorithms. - Apply appropriate statistical techniques or advanced machine learning models to address research questions and interpret the findings of analysis. - Working independently or with a data engineering team to select, create and preprocess analytic dataset(s. - Engage with scientists/grantees and Association scientists and clinical and research volunteers to define research questions, develop analysis plans, and write summary reports. - Involve in technical innovation through active research and applications of new theories, techniques, and technologies such as machine learning, deep learning /AI models (e.g., neural networks, convolutional neural networks, large language model) for complex clinical data analysis and prediction. - Publish journal papers and present work at scientific meetings. - Attend relevant external conferences, and attend/co-lead consultative sessions with volunteer Task Force and other Association volunteers/experts. - Contribute expertise to communication strategies, including engagement networks, written pieces, workshops, and publication plans. Qualifications: - Master’s degree or above in Data Science, Computer Science, Biostatistics, Statistics, Biomedical Informatics, Engineering, or a related field. - Two (2) years of experience in programming, especially Python and R. - Demonstrated aptitude for data analysis, programming, and creative problem solving. - Proficiency in statistical modeling and machine learning algorithms. - Experience with data cleaning, curation, and preprocessing. - Experience with SQL and database. - Familiarity with handling large-scale datasets in the clinical domain, including electronic health record data, research cohort, and/or clinical dataset. - Excellent written and oral communication skills, with the ability to effectively communicate technical information to both technical and non-technical stakeholders. - Highly effective organizational skills, time management, responsibility, and motivation. Preferred Experience: - Experience in cardiovascular data analysis. - Experience working in a healthcare or research environment. - Experience with version control or cloud computing. - Extensive experience in publishing research findings in high-impact journals