Computer Systems Analyst

Axle•Baltimore, MD

14h•$95,000 - $105,000

About The Position

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. 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.

Requirements

Minimum Education: Bachelor
Skills
Scientific Data analysis
Algorithm development
Statistical modeling
Database management
Data visualization
Data presentation
Machine learning
Data annotation
Exome analysis
Data cleaning
Data analysis
Data mining
Research
Scientific Computing using GPU
Website Development
Maintenance
Imaging
LIMS

Nice To Haves

Certifications & Licenses Preferred
Master's Degree
Field of Study
Genetics
Software
BioConductor
Scikit-learn
Javascript
Matplotlib
TensorFlow
RMarkdown
Ggplot2
MongoDB
PyTorch
MATLAB
Nodejs
Oracle
Pandas
Plotly
Python
Scrapy
SQLite
Dplyr
HTML5
Keras
Linux
MySQL
NoSQL
NumPy
SciPy
Shiny
PHP
JavaScript
STATA
Bash
HTML
Java
Perl
SPSS
Unix
C++
Git
SAS

Responsibilities

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.
Provides 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.
Sets up and uses various computer systems and software packages.
Provide performance tuning, hardware upgrades, and resource optimization across the full range of scientific high-performance computing architecture.
Provide software solutions across diverse scientific applications including large and complex multi-component resources.
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.
Compiles and manages data and assists with quality control.
Develop custom computer applications for collecting and analyzing data, including some that interface with commercial and custom built hardware.
Perform troubleshooting, interpretation of results and analysis.
Utilize knowledge of data structure, data management and various programming language.
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.
Produces 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.
Trains users in applying systems and analysis methods.
Plan, organize and coordinate formal and informal IT related training and orientation of IT initiatives.
Support and train users in applying data analysis pipelines and methods for research studies.
Conduct educational courses on basic scientific computing, data analysis scripts and pipelines.
Consult and collaborate with users to explain new tools and enable them to be adapted to meet specific research needs.
Maintains systems software as well as hardware and security configurations.
Support and maintain commercial scientific software and freeware relevant to analyses and scientific discovery.
Maintain system software, hardware configuration, and security, as well as upgrade of the software as necessary to maintain security.
Deploy security measures to maintain integrity of data.
Maintains interface software between multiple computer environments to ensure smooth operation and communication.
Perform routine audits of tracking database and packages.
Collaborate with staff to increase the productivity/efficiency of data analysis using high-performance computing.
Develops new programs and systems as needed.
Design and maintain data analysis pipelines for research data.
Develop customized software to detect and measure specific structures and events of interest for statistical analysis and testing specific hypotheses.
Create specialized computer software to effectively and automatically analyze experimental data.
Develop dedicated and efficient computer software using state of the art computer science approaches, including modern programming languages and coed libraries, machine learning, cross-platform programming, and high-performance computing.
Develop scripts to automate data processing pipelines.
Develop and implement new or major revisions to applications, databases, or software tools.
Research new technologies, standards and systems to improve existing products and websites.
Coordinates data storage and mining.
Manage a data storage and backup for scientific computers using available resources.