Application Programmer/Analyst Intermediate
How to Apply
A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
The scientific programmer will support a highly-interactive research team in the Michigan Genomics Initiative (MGI) at the University of Michigan School of Public Health. MGI is involved in cutting edge genetics research, studying genetic variation in humans, with a focus on understanding how genetic variation contributes to the risk of common human diseases such as diabetes, heart disease, and psychiatric illness. MGI participates in many aspects of the design and analysis of genetic studies, ranging from the development of interactive applications for tracking ongoing studies to the development, distribution, and maintenance of free software for the analysis of genetic data. This is an opportunity to work in a challenging and rewarding research area that constantly poses new technical and computational challenges. This posting is reflective of the intermediate level. We will also consider candidates at the senior level, based on desired education and experience. The Senior range is 80,546-99,498 .
The group is seeking a full stack applications programmer who will focus on our web interfaces for querying and processing of terabytes of data. In this capacity, you will help develop, enhance, and maintain web-based applications that manage the submission, scheduling, and reporting of big data processing tasks.
- Support, maintain, and enhance both front and back-end applications using scalable, portable, and standards-compliant code.
- Provide support to end users. Ensure tools are robust and friendly in the face of user and input errors.
- Incorporate user and partner feedback and communicate with them.
- Provide technical advice to faculty, students, and staff within our research team.
- Participate in the execution and completion of scientific research projects.
- Bachelor’s degree in computer science, engineering, or an equivalent combination of education and experience.
- Experience working with RESTful web APIs, both as a consumer and provider.
- Ability to troubleshoot web server performance.
- Familiarity with data analysis pipeline best practices.
- Minimum of 3-5 year of relevant experience in a related role displaying strong personal initiative, a drive for continuous improvement, demonstrated end-to-end responsibility for mission-critical services, and excellent problem-solving skills.
- Fluency in web security best practices.
- Excellent communication skills.
- Familiarity with Linux, command-line programming, and high-performance computing.
- Demonstrated experience using Linux shell scripting tools (e.g. bash, awk, grep) to design reproducible data cleaning and/or analysis pipelines.
- Knowledge of standard statistical analysis (e.g. linear and logistic regression).
- Master’s degree in computer science, bio-statistics, bioinformatics, statistics, mathematics or related field
- Coursework in applied statistics.
- 1-2 years of experience using Python for data analysis.
- Development and management of production web applications with large numbers of diverse users.
- Experience with software version control systems such as Git.
- Experience performing genome-wide association studies.
- Experience with modern development methodologies such as agile development and test/behavior driven development.
We are seeking an experienced and dynamic staff (leader/member) with a commitment to contributing to a diverse, equitable and inclusive environment for all members of our community.
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.