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Lead Analyst Data Science

Organization
ASU-UA Collaboration Institute for Future Health
Job Location
660 S Mill Ave
Tempe, AZ 85281
United States
Job Description

Description:

 

The ASU-UA Collaboration Institute for Future Health (IFH) is seeking to fill three (3) new Lead Analyst Data Science positions for Remote Sensing, Advanced Analytics and Large Scale Biological Datasets.

 

Under senior administrative direction of the Deputy Director the Lead Analyst Data Science will be responsible for managing, planning, supporting and preparing data analysis and reports focused on the focus topic assigned. The data generated will be used for business decision-making, strategic planning, and process improvement to support the growth of the ASU-UA Collaboration Institute for Future Health (IFH). The area of advanced analytic techniques, including but not limited to program management of artificial intelligence tool development, machine learning methods, neural networks and advanced bioinformatics tool development to support remote sensing capabilities.

 

Essential Duties:

 

Knowledge of principles and practices pertaining to artificial intelligence tool development and machine learning as it applies to the practice of medicine. Ability to evaluate the development of advanced analytic tool technology and to identify analytic tools that have the greatest potential impact on future healthcare. To work with university scientists developing advanced analytic tools to explore new health related applications for analytic methods. Deep knowledge of the artificial intelligence and machine learning industrial research. Knowledge of advanced analytic methods and tools currently available for healthcare applications, methods and tools that are currently available for non-healthcare applications.  

 

Performs data analysis, to understand current performance, analyze trends, and to make recommendations for future project performance related to advanced analytic methods and technology. Develops measurements and metrics for data analysis 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 supplier data (e.g. industry trends, supplier performance and cost dynamics); prepares supplier reviews. 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 customer feedback. Prepares or coordinates preparation of reports; analyzes and interprets statistics, financial data, and management planning data for predicting resource needs and developing long range plans. Prepares presentations to stakeholders and university administration. Conducts and assists with the development of long-and short-range goals. Represents the department/college and serves 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.

 

Desired Qualifications, Knowledge, Skills and Abilities:

  • Knowledge of principles and practices pertaining to the development of advanced analysis methods and technology, in particular artificial intelligence, machine learning, neural networks and other advanced bioinformatics analytic tools related to analyzing and integrating a variety of data types for healthcare purposes.
  • Such datasets could include remote sensing technology, genomic information, electronic health records and imaging technologies.
  • Knowledge of analysis techniques and reporting strategies
  •  Knowledge of computing and data analysis
  • 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.

 

Working Environment:

Activities are performed in an environmentally controlled office setting subject to extended periods of sitting, keyboarding and manipulating a computer mouse; required to stand for varying lengths of time and walk moderate distances to perform work. Occasional bending, reaching, lifting, pushing and pulling up to 50 pounds. Regular activities require ability to quickly change priorities, which may include and/or are subject to resolution of conflicts. Ability to clearly communicate verbally, read, write, see and hear to perform essential functions.

 

Minimum Qualifications:

PhD expert in advanced analytic methods and technology as it relates to remote sensor and healthcare data, plus proficiency in Statistics, Computer Information Systems, Business Information or a related field and five (5) years of related administrative/data analysis experience which includes one (1) year of supervisory experience, OR, any equivalent combination of experience and/or education from which comparable knowledge, skills and abilities have been achieved. Must have the experience and ability to manage collaborations with scientists and companies developing advanced analytic tools for healthcare.

 


 

How to Apply

Application Instructions

Application deadline is 3:00PM Arizona time on December 7, 2020. Applicants are responsible for including a cover letter, CV, and the names of three professional references in their application through ASU career website. Emailed applications will not be accepted.

  • 64136BR              Lead Analyst Data Science, Remote Sensing – Apply here
  • 64137BR              Lead Analyst Data Science, Large Scale Data – Apply here
  • 64138BR              Lead Analyst Data Science, Advanced Analytics – Apply here