Description
Description
The Customer has an environment dedicated to tradecraft innovation and is a unique addition to the Intelligence Community (IC). This office incorporates new and emerging commercial technologies, along with tailored and specific technical and analytic capabilities in order to achieve its core mission. Partnerships with tradecraft schools and mission elements drive discovery and definition of projects suitable to Customer's capabilities. The Customer provides an environment for concept incubation, prototype evaluation, and pilot execution in the effort to advance technical intelligence, tradecraft, capabilities, and techniques. The efficiencies gained by collocating technical tradecraft capabilities with new employee training and development provides a comprehensive perspective of exactly what new employees may encounter when they go to the field.
CORE COMPETENCIES:
- Data Science Support - Work to incorporate AI/ML into systems to address Customer key intelligence questions. Uses development tools such as Python, leverage statistical reasoning and methods to critically assess datasets and the validity of data science findings. Requires familiarity with intelligence collection approaches, Customers tradecraft, analytic lifecycle, or a demonstrated ability to engage Customer's mission partners to understand and anticipate their priorities.
Qualifications
Data Scientist
Required Skills:
TS/SCI with Polygraph
1. Demonstrated experience with deploying and developing cloud-based systems from the ground up using CloudFormation and Cloud Development Kit (CDK) with services including: • Elastic Map Reduce (EMR) • Elastic Compute Cloud (EC2) • Fargate • Application Load Balancer (ALB) • Simple Storage Service (S3) • Route53 • Relational Database Service (RDS) • Identity Access Management (IAM) • Simple Notification Service (SNS) • Simple Queue Service (SQS) • Lambda • Elastic Block Storage (EBS) • CloudWatch • CloudTrail • Config • Secret Manager • Key Management Service (KMS)
2. Demonstrated experience with deploying and developing Spark Streaming
3. Demonstrated experience deploying Dockerized Python micro services with FastAPI.
4. Demonstrated experience developing and deploying machine learning algorithms with Scikit-Learn, SciPy and MUKH.
5. Demonstrated experience deploying Docker containers for staged applications.
6. Demonstrated experience using Git and Gitlab.
7. Demonstrated experience collecting and managing requirements from users in a formal and adhoc manner.
8. Bachelor's Degree or 4 years' experience in Computer Science or related field.
SAIC accepts applications on an ongoing basis and there is no deadline.
Covid Policy: SAIC does not require COVID-19 vaccinations or boosters. Customer site vaccination requirements must be followed when work is performed at a customer site.
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