SAIC is seeking to solve business problems through the development of prototypes of emerging technologies, specifically AI/ML/NLP and data modeling, in cloud native environments.
Requirements
- 7 years or more of experience in data analytics, data modeling, machine learning, natural language processing, security, and artificial intelligence technologies in cloud native environments (AWS, Azure, Google)
- Cloud engineering experience to ensure integration of the AI/ML/NLP solutions in cloud native environments
- Experience with emerging technologies, modernization, and innovation opportunities
- Knowledge of cybersecurity policies and compliance standards including Authorization To Operate (ATO) certifications
- Experience with predictive models, machine learning algorithms, and statistical analyses
- Experience with data architecture best practices
- Experience with Agile product teams and integrating and operationalizing emerging technologies and data strategies
Responsibilities
- Operate and maintain an innovation lab for the ideation, design, and engineering of cloud native product modernization and innovation using emerging technologies.
- Develop end-to-end plans for cloud native AI/ML/NLP innovations that are compliant with cybersecurity policies.
- Develop and engineer pilots, prototypes, and proof of concept solutions to validate emerging technology, modernization, and innovation opportunities.
- Implement predictive models, machine learning algorithms, and statistical analyses to solve complex business problems.
- Conduct exploratory data analysis and generate actionable insights from large and complex datasets.
- Develop reusable code libraries and best practices for modernization and innovation development and deployment.
- Analyze data and usage to find patterns and solutions to business challenges.
Other
- BA/BS degree
- Must be able to obtain a Public Trust
- US Citizenship not required, but must have lived in the US for at least two consecutive years
- Ability to present business briefings, recommendations, and demonstrations to executives and technical stakeholders in a clear manner
- Ability to mentor more junior data scientists and guide the team in adopting new technologies and techniques
