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Data Analyst

2 months ago

Aurora, Colorado, United States Kaiser Permanente Full time
Job Summary

We are seeking a highly skilled Data Specialist/SAS Program I to join our team at Kaiser Permanente. The successful candidate will work closely with biostatisticians and programmers to manage all aspects of data manipulation, ensuring data quality and maintaining data integrity for analytic studies or the research data warehouse.

Key Responsibilities
  • Develop solutions to routine problems, following established policies and procedures, and provide information to others to be used in decision-making processes.
  • Assist in data management, including planning and carrying out data management activities, such as data cleaning/quality assurance, data documentation, and analytic data set creation.
  • Operationalize research protocols, participate in multi-site projects, and identify and resolve problems using interactive problem-solving and troubleshooting techniques.
  • Develop QA programs to identify any issues in the data, partner with members of the research team to resolve data issues, and notify appropriate IHR subject matter experts of issues discovered in the data.
  • Extract data from multiple sources within KP, develop a thorough understanding of the data elements to be used for a study, and communicate issues around the data elements and propose alternatives to make the data as complete and accurate as possible.
  • Independently author programs to efficiently extract data from source systems using a variety of SAS tools, as well as other analytic programming languages, such as Python, R, or SQL.
  • Contribute to programming for KPCO or for multi-site research collaborations or research data warehouse ETL.
  • Provide the data for study development or manuscript preparation, i.e., analytic data sets.
  • Demonstrate experience in relational database structures, system testing, and quality assurance methods.
  • Participate in the development of registries/databases, including base definition, structure, documentation, long-range requirements, operational guidelines, and protection.
  • Ensure accuracy and completeness of data in master files and various support tools, such as data dictionaries, to be used by the research team.
  • Coordinate data transfers and data reconciliation, comply with IRB-approved protocols, Business Associate Agreements, and Data Use Agreements to transfer data between agencies.
  • Employ data management best practices and knowledge thereof in a standardized, transparent, and efficient manner.
  • Assume responsibility as a partner for the planning, resourcing, and execution of relevant internal and external data management activities to obtain clean databases within a specified timeframe.
  • Openly review code with team members to ensure high-quality results and share techniques employed.
  • Develop knowledge and professional skills through continuing education, cross-training, literature, and attendance at departmental meetings.
  • Assist with proposal development under the scientific direction of a PI.
  • Assist with data interpretation, preparation of technical reports, manuscripts, posters, and presentations.
  • Adhere to federal and local regulations and KPCO Standard Operating Procedures governing research, maintain compliance when manipulating large volumes of patient data, and follow the IRB-approved protocols on federally funded grants as well as on internally funded projects.
Requirements
  • Minimum one (1) year of SAS, R, Python, or SQL experience.
  • Bachelor's degree required.
  • Highly organized with an emphasis on attention to detail and quality control.
  • Ability to adapt to constantly changing environments and priorities.
  • Excellent interpersonal, verbal, and written communication skills required.
  • Healthcare/research experience preferred.
  • SAS programming experience preferred.
  • Masters degree in social or behavioral sciences, health services, public health, statistics, health economics, epidemiology, computer science, or related field preferred.