Data Scientist

Integral•, DC

About The Position

The Data Scientist supports all Data Acquisition, Analytics, and Governance Services tasks and the strategy, design, and deployment of all advanced analytical and AI/ML models for the Office of Naval Research (ONR) Comptroller’s Office Data and Analytics (D&A) Division architecture.

Requirements

Bachelor’s Degree in computer science or IT related degree with 10 years experience
Ten (10) years of experience developing and deploying analytical models to address Science & Technology (S&T) or business requirements within a Department of War (DoW) organization.
Five (5) years of hands-on experience using Python or R for statistical analysis, predictive modeling, and developing artificial intelligence/machine learning (AI/ML) models.
Verifiable project experience developing data pipelines for batch or streaming data processing, including data cleansing, standardization, and normalization.
Experience on at least two (2) distinct projects that required the application of advanced analytical techniques (such as Natural Language Processing (NLP), Network Analysis, or Bibliometric Analysis) to S&T portfolio data.
Secret Clearance.

Responsibilities

Provide comprehensive technical infrastructure support for all systems supporting the data and analytics environment.
Design, deploy, and operate all data and applications within a cloud environment authorized at the FedRAMP High baseline and DoD Impact Level 5 (IL5), and maintain the system’s Authority to Operate (ATO) at all times lo include configuration management, security patching, system monitoring, and help desk support.
Support the architecture design for scalability to accommodate future growth in data volume and user load.
Sustain secure data access mechanisms, including Application Programming Interfaces (APIs) and user interfaces for data exploration, as well as a secure Bulk Data Download capability for authorized users.
Manage access mechanisms under a formal data governance framework, including metadata management and data cataloging.
Develop and deploy machine learning (ML) and artificial intelligence (AI) models, including Natural Language Processing (NLP) to analyze unstructured text and the integration of AI/ML platforms (e.g., AWS SageMaker, Azure Machine Learning).
Automate infrastructure and workflows using Infrastructure as Code (IaC) tools (e.g., Terraform, Ansible), build and manage CI/CD pipelines for secure software deployment, and develop streaming data pipelines (e.g., using Apache Kafka or AWS Kinesis) for real-time data processing.