Computer Systems Analyst Baltimore, MD

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision‑making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Axle is seeking a Computer Systems Analyst to join our vibrant team at the National Institutes of Health (NIH) supporting the The National Institute on Aging (NIA) in Baltimore, MD.

• Paid Time Off and Paid Holidays
• 401K match up to 5%
• Educational Benefits for Career Growth
• Employee Referral Bonus
• Flexible Spending Accounts:
  • Healthcare (FSA)
  • Parking Reimbursement Account (PRK)
  • Dependent Care Assistant Program (DCAP)
  • Transportation Reimbursement Account (TRN)

Overall Position Summary and Objectives

The purpose of this position is to support research within NIA‑IRP including recording and cleaning data, data analysis, computer server maintenance, website maintenance and software development and installation.

• Meet with lab members to present updates - Weekly
• Patch and update server software - Monthly

• Support and maintain scientific computer systems including hardware, operating systems, and associated services in a high‑performance computing environment.
• Provide systems analysis and bioinformatics support for large scale sequencing projects.
• Perform algorithm development and implementation.
• Perform statistical analysis of experimental data obtained at various time points.
• Develop and test web applications.
• Provide technical experience needed to perform analyses, processing and user support of various computer systems using standard statistical procedures and techniques.
• Provide statistical support to staff, including data analysis and the generation tools for researchers to use.
• Provide support and consultation in the areas of scientific computation, application‑development and computer modeling.
• Design, develop, document, analyze, create, test and modify computer systems, programs and integrations.
• Set up and use various computer systems and software packages.
• Perform performance tuning, hardware upgrades, and resource optimization across the full range of scientific high‑performance computing architecture.
• Collaborate with staff to increase the productivity/efficiency of data analysis using high‑performance computing.
• Implement improvements to development activities to speed development of applications, databases, or software tools.
• Determine needs and provide IT support for computerized systems supporting activities.
• Work with staff on the evolving infrastructure, data engineering pipeline, and data science stacks.
• Compile and manage data and assist with quality control.
• Develop custom computer applications for collecting and analyzing data, including some that interface with commercial and custom built hardware.
• Utilize knowledge of data structure, data management and various programming languages.
• Manage data formatting input and output.
• Perform quality assurance and quality control; troubleshoot issues with image analysis and quality.
• Analyze results of the data that are collected during experimental studies; perform statistical analysis using statistical analysis software.
• Drive collection of new data and the refinement of existing data.
• Produce various reports, graphs and figures for presentation.
• Prepare data and analysis for presentations and publication.
• Present results in graphical using appropriate language.
• Prepare research data for presentation and manuscripts.
• Interface with the statistical programming team to develop programming standards and assist the team with validation and change control documentation.
• Enhance efficient and effective presentation of information, content, images and graphics online and through the digital platforms.
• Train users in applying systems and analysis methods.
• Pla…