SAIC is looking for team members to support the Defense Intelligence Agency (DIA) Transforming All-Source Analysis with Location-Based Object Services (TALOS) to advance the state of the art in Big Data, data analysis, Artificial Intelligence (AI), Machine Learning (ML), and advanced analytics to enhance the DoD’s and the Intelligence Community’s (IC) information processes and technical architectures. DoD and the IC, warfighters, policymakers, and acquisition leaders must address strategic challenges that focus on leading-edge IT to deliver insight, advantages, and dominance in all warfighting domains including land, maritime, air, space, and cyber.
The candidate will support the lifecycle of data within DIA from the time it is acquired to the time it is removed from DIA’s systems, and support development, maintenance, and sustainment of the customer’s all-source data enterprise architecture. This includes providing data management through formatting, indexing, and storage of all data repositories. In addition, the contractor shall support, maintain, and manage the data repositories, tools and software within the agency enterprise architecture as well as support the transition to suitable cloud environments.
Additionally, the candidate shall provide specialized and highly technical support to identify and incorporate emerging data sources and metadata into the programs through research and development. The candidate will support integration object detection hardware and models into the existing production data collection environment and transition existing platforms, data repositories, and architectures to target architecture and data access Application Programming Interfaces (API).
Works in cross-functional teams with data at all stages of the analysis lifecycle to derive actionable insight. Translates mission needs into an end-to-end analytical approach to achieve results. Performs the pre-analytics areas of data collection and understanding, data cleansing and integration, and data storage and retrieval. Determines the appropriate analytics based on the data and the desired outcomes, using techniques including feature detection, statistics, data mining, predictive modeling, machine learning, natural language processing, and business intelligence. Interprets the validity of results and communicates the meaning of those results. Has familiarity with data wrangling, analytics, and visualization software and programming languages, including analytics methods for big data. Follows a scientific approach to generate value from data, verifying results at each step.