As part of Guidehouse's Advanced Data Analytics team, you will work on high-impact and high-visibility projects, helping to shape not only Guidehouse's current business, but its long-term strategy.
Build the future of Data Science as part of the Artificial Intelligence Center of Excellence (CoE). The CoE is a unique team within Guidehouse, focusing on solving our client's most critical challenges using Data and Advanced Analytics, AI, and Automation. The CoE works on a wide variety of projects; from predictive analytics models to support our healthcare, financial, and energy services divisions, to open source analysis for federal agencies, to applying a variety of deep learning models (ie, NLP, image recognition) to solve more complex problems.
This role involves working in a complex, multi-functional, Agile team environment with other data scientists, engineers, and UI/UX developers to develop and productionize analytics solutions. As a full stack engineer on the team you will work side-by-side with an experienced team of UI designers, Back End machine learning engineers, data scientists, and product managers to develop cutting edge AI solutions to tackle some of the federal government's biggest challenges.
Write performant, maintainable code that is easy to read and well-documented
Configure CI/CD pipelines to automate code testing and deployment
Collaborate closely with other developers and members of the Guidehouse Analytics team
Deploy code via Docker/Kubernetes/Helm on Amazon Web Services (AWS)
Participate in lean/agile development process that focuses on customer value delivery, low latency engineering practices, and individual developer ownership
Security Clearance: None
Minimum Years of Experience: 2
Education: Bachelor's Degree from an accredited university
2+ years software development experience in any Scripting language
2+ years DevOps technology experience, eg Docker, CI/CD pipelines, Kubernetes, Infrastructure as Code
1+ years of Database (SQL and/or NOSQL) experience
Experience building solutions in a cloud environment (preferably AWS)
Experience supporting data science workloads
Experience with AI/ML and Analytics technologies and workloads
Familiarity with Cloud Native design and development principles
The successful candidate must not be subject to employment restrictions from a former employer (such as a non-compete) that would prevent the candidate from performing the job responsibilities as described.