Early Career Python Programmer​/Analyst

Why RTI

RTI International is an independent, scientific research institute dedicated to improving the human condition. Our vision is to address the world’s most critical problems with technical and science-based solutions in pursuit of a better future. Clients rely on us to answer questions that demand an objective and multidisciplinary approach—one that integrates expertise across social, statistical, data, and laboratory sciences, engineering, and other technical disciplines to solve the world’s most challenging problems.

We believe in the promise of science and technical solutions, and we push ourselves every day to deliver on that promise for the good of people, communities, and businesses in the US and around the world. If you are looking for the opportunity to make a real difference, RTI is the place for you.

RTI’s Center for Data Interoperability is seeking dynamic and detail-orientated candidates for a full-time Programmer/Analyst with Python or SQL analytic programming experience. The Programmer/Analyst will work with researcher teams to analyze and synthesize complex qualitative and quantitative administrative health data from multiple sources into meaningful results. Individuals in this role will provide analytic development and statistical programming knowledge to project teams conducting research using healthcare data, especially large and complex health insurance claims and survey data, in a fast-paced environment.

This position is based in Research Triangle Park, NC or any other U.S. location as a telecommuter.

Approximately 90% of working time will require:

• Developing coding expertise and best practices to query, merge, and analyze complex healthcare data from large relational databases
• Leveraging a variety of quantitative methods to standardize, blend, and distill data from multiple disparate sources, transforming them into analytic insights for use in client reports, journal manuscripts, abstracts, or posters for professional meetings
• Iteratively developing and maintaining Python code while adopting best practices for increasing efficiency, minimizing computational errors, implementing process improvements, and other approaches that add value to business processes and analytic results
• Participating in thorough code review and documentation, as well as parallel coding efforts for other programmers to maintain quality standards and ensure that code may be efficiently transferred among team members as needed
• Constructing analytic datasets and databases to support deliverables for various public health and healthcare financing engagements
• Collaborating with project team members to review, critically evaluate, and refine business requirements, and then translate those requirements into programming logic
• Adopting and refining technical skills on projects, including working independently, proactively resolving day-to-day issues of small complexity, and leveraging coding best practices and standards

Approximately 10% of working time will require:

• Participating in continuing education courses on healthcare-related and/or technical coding topics (including learning new coding languages) as applicable to the role and evolving business needs
• Sharing insights gained from the above activities with fellow programmers, leaders, and other division staff through activities such as presentations at staff meetings, contributions to collective codebase utilities, and training early career staff

Minimum Qualifications:

• BS/BA or advanced degree in data science, computer science, statistics, social sciences, health policy or related field with an emphasis on analytic programming using Python or SQL.
• Minimum of 1 year of academic experience with Python or SQL analytical coding with demonstrated familiarity with the linkage of various types of data files.
• Experience designing and implementing flexible, reusable, scalable programming code.
• Commitment to analytic programming quality and best practices, including experience with QA/QC procedures (e.g., peer review of code, parallel programming).
• Familiarity with all phases of the Analytic Development Life Cycle and…