R Programmer (Washington, DC)

Unclassified - Washington, DC

Full-time - Mid Level

Washington, DC

About the position

The Data Engineering and Advanced Analytics Enablement team is seeking an R Analytics Cloud Engineer to play a pivotal role in enhancing the analytics tools utilized by the research community. This position focuses on supporting the migration of analytics applications to the cloud and implementing significant transformational changes in the deployment of analytics tools through cloud-native architecture. The successful candidate will be responsible for assessing, designing, and building workflows that integrate solutions for scalable, reliable, and automated R analytics data science products on AWS. In this role, you will develop data science tools using R Shiny as the web framework and deploy these artifacts into RStudio Connect through continuous integration and continuous delivery (CI/CD) processes. You will also design, develop, test, and support R programs that execute modeling application systems via distributed computing on AWS. Additionally, you will assist business applications in deploying models into the cloud using containerization technologies such as Docker and Kubernetes. A strong emphasis will be placed on automated deployment, infrastructure automation solutions, and continuous delivery processes. You will leverage various analytics data platform tools, including RStudio on Domino/Sagemaker, RStudio Connect, and AWS services, to build workflows that support the deployment of analytics applications developed in R. Participation in an on-call rotation for critical outages and issues is also expected. The role requires strong hands-on experience with shell scripting (Bash, Csh, Ksh) and effective communication and technical skills. You will be responsible for developing and maintaining technical documentation, including system diagrams and operational procedures.

Responsibilities

• Assess, design, and build workflows to integrate solutions for scalable, reliable, and automated R analytics data science products on AWS.
• Develop data science tools with R Shiny as the web framework and deploy the artifacts into RStudio Connect via CI/CD.
• Design, develop, test, and support R programs to execute modeling application systems via distributed computing on AWS.
• Support business applications in deploying models into the cloud with containerization technologies such as Docker and Kubernetes.
• Support the team in writing deployment scripts with a strong emphasis on automated deployment and infrastructure automation solutions.
• Leverage Analytics Data Platform tools (RStudio on Domino/Sagemaker, RStudio Connect) and AWS services to build workflows that support deployment of analytics applications developed in R.
• Participate in an on-call rotation for critical outages and issues.
• Develop and maintain technical documentation including system diagrams and operational procedures.

Requirements

• 5+ years overall experience in IT related experience including software development, Data Scientists & DevOps functions.
• 3+ years solid development experience in R, R packages, RStudio, RStudio Connect, RStudio Package Manager, Python, SQL, Web & Cloud Technologies.
• 2+ years of experience with AWS services supporting data science and analytics (EC2, S3, RDS, Lambda, Sagemaker, Glue).
• 2+ years of relevant working experience in an analytical role involving data extraction, analysis, and communication of findings.
• 2+ years of experience in building and maintaining CI/CD tooling (Jenkins, Bitbucket Pipelines, GitHub).
• Experienced in Data Exploration packages with Base R.
• Experienced in using deep learning frameworks such as TensorFlow, Pytorch, etc.
• Ability to effectively communicate technical solutions to engineering teams and business audiences.

Nice-to-haves

• Knowledgeable in the AWS Well Architected Framework.
• Strong analytical, organizational, problem-solving, and time-management skills.
• Strong communication (verbal and written) and listening skills.
• Strong teamwork, planning, and coordination skills.
• Self-motivation, adaptability, and the ability to meet aggressive deadlines.
• Ability to independently research and resolve technical problems in a complex IT environment with local and remote groups.