Lead Analyst, Large Scale Data Analytics
Basic/clinical research in biomedical data science is under the administrative direction of the Deputy Director of the Institute of Future Health (IFH), a joint Arizona State University/University of Arizona research institute. The Lead Analyst Data Scientist for Large Scale Data Analytics will be responsible for managing, planning, supporting and preparing large scale data for analysis and reports focused on the accrual, formatting, data basing and quality control of large clinical datasets. In collaboration with a team of data specialists in the field of remote sensing for cardiovascular disease, digital psychiatry and infection disease and experts in machine learning and artificial intelligence the Lead Data Scientist for Large Scale Data Analytics will help to develop methods to analyze clinical data for the prediction of disease outcomes. In addition to use for scientific advancement and publication, the data generated will be used for business decision-making, strategic planning, and process improvement to support the growth of the Institute for Future Health. The area of advanced analytic data techniques includes but is not limited to the development of data management and data analysis in the areas of digital psychiatry, congestive heart failure and infectious disease.
Knowledge of principles and practices pertaining to the proper accession, formatting, storage, and QC analysis of clinical and molecular data as it applies to the practice of telemedicine.
Ability to evaluate the development of novel data handling and storage methods and advanced analytic tool technology that will have the greatest potential impact on the future of telemedicine. To work with university scientists developing advanced analytic tools to explore new health related applications for analytic methods. Deep knowledge of data structure, databases, data quality required for advanced analytics, and cloud-based data storage is required.
Enables analysis on databases by team of data analyst. To make recommendations for future project performance related to advanced data handling methods and technology. Develops measurements and metrics for data quality to be used for business decision-making, planning, and process improvement. Securely collects, cleanses, standardize, transforms and stores data from various sources ensuring data integrity. Directs the collection of data. Uses predictive modeling, statistics, trend analysis and other data analysis techniques to collect, explore, and identify the right data to be analyzed from internal and external sources. In collaboration with other data scientists in the Institute, creates and maintains statistical reporting tools to support the specific discipline. Responsible for regularly auditing data input; audits may involve studying number, organization practices and sponsor feedback. Prepares or coordinates preparation of reports; analyzes and interprets statistics, financial data, and management planning data for predicting stakeholders and university administration. Conducts and assists with the development of long-and short-range goals. May represents the department/college and serve on various department and university committees. Maintains broad awareness of current trends in data collection and organization, data preservation, and numeric data analysis by participation in appropriate professional activities and contributing to research in the field. Will implement procedures and technologies that assure the long-term sustainability and accessibility of datasets. May supervise, monitor or coordinate the activities of subordinates to ensure adherence with stated outcomes, timeframes and standards. Reviews job performance in conjunction with established unit, department and university goals. Utilizes various computer programs and software to perform data computation, statistical analysis and other data manipulation activities. May perform other duties as assigned.
Doctoral qualification (PhD, MD, or DVM) and 5-years’ experience in large research project management in academia, bio industry, government, or healthcare organizations in one or more areas of the biological sciences, biomedicine, bioinformatics, sensor technologies, molecular diagnostics, precision medicine, digital health and remote patient monitoring and related experience in strategic planning, program planning and execution and familiarity with public and private sector funding agencies.
Knowledge of principles and practices pertaining to the collection and storage of clinical data, remote biosensor data, imaging data, genomic data, etc.
Knowledge data curation as it relates to data analysis techniques Knowledge of computer and data storage infrastructure Knowledge of data management and information technologies Knowledge of supervisory principles practices and techniques
Knowledge of the principles of exemplary customer service demonstrated through actively listening, acknowledging, and responding to every inquiry; taking ownership and resolving each concern or problem as appropriate; exhibiting professionalism and expertise in every interaction and engaging in professional development to meet expectations for service excellence. Skill in quantitative data analysis and interpretation.
Knowledge of the principles and practices pertaining to the assigned department Knowledge of administrative, financial, and business management principles and practices
Skill and ability to collect, organize, synthesize and analyze data; summarize findings; develop conclusions and recommendations
Skill in planning, analyzing, and coordinating activities and establishing priorities Skill in managing multiple priorities, adhering to deadlines and allocating
Ability to accurately and reliably interpret data for determining appropriate action
Ability to influence changes in individual, institutional, and/or corporate behaviors to create a more sustainable environment
Ability to effectively communicate results of analysis, novel ideas and project updates to senior management, peers and collaborators
Ability to design, build and maintain databases of information related to the development of advanced analytic tools by external companies and university scientists. Understands the importance of metadata as it applies to development of advanced analysis methods and technology.
The Institute for Future Health (IFH) is a joint venture between Arizona State University (ASU) and the University of Arizona (UA) to redefine healthcare. The IFH will be a research and clinical hub to integrate the convergence of biomedicine, engineering and computing for
innovation in precision health and digital health and their dependence on proficient capture, analysis and use of rapidly expanding large-scale data. Inter-disciplinary project teams from both universities and clinical and corporate partners will develop new sensor and wireless platforms for remote monitoring of health status, interactive telemedicine and the application of cognitive computing in patient care to improve diagnosis, monitor treatment adherence, reduce hospital readmissions and maintain wellness. The initial projects will focus on cardio-pulmonary diseases, mental health and infectious disease surveillance.
Arizona State University is a new model for American higher education, an unprecedented combination of academic excellence, entrepreneurial energy and broad access. This New American University is a single, unified institution comprising four differentiated campuses positively impacting the economic, social, cultural and environmental health of the communities it serves. Its research is inspired by real world application blurring the boundaries that traditionally separate academic disciplines. ASU serves more than 80,000 students in metropolitan Phoenix, Arizona, the nation's fifth largest city. ASU champions intellectual and cultural diversity, and welcomes students from all fifty states and more than one hundred nations across the globe.
Arizona State University is a VEVRAA Federal Contractor and an Equal Opportunity/Affirmative Action Employer. All qualified applicants will be considered without regard to race, color, sex, religion, national origin, disability, protected veteran status, or any other basis protected by law.