Data Scientist

SAIC • Town of Cortlandt, NY

16d • Onsite

About The Position

SAIC is seeking a Data Scientist located at Camp Smith in Hawaii to support the USPACOM J7 Directorate. The role involves managing the collection, cleaning, processing, and analysis of large datasets to extract insights and ensure data integrity and accuracy. The Data Scientist will represent J7 Directorate interests in high-level battle rhythm forums, align strategic objectives with command-wide priorities, and lead the integration of AI within the Joint Exercise Program to modernize training methodologies and readiness. This position will orchestrate J7 data science initiatives from conception to delivery, aligning technical development teams with leadership priorities to ensure the on-time deployment of mission-critical data solutions. Responsibilities include developing and deploying predictive models, algorithms, and real-time support systems for operations, enhancing efficiency and providing actionable insights. Collaboration with cross-functional teams to identify data-driven opportunities, conduct research, apply emerging technologies, and optimize dashboards for stakeholder communications is key. The role also involves architecting and maintaining robust data models and schemas, ensuring the reliability and scalability of enterprise-level data pipelines, and collaborating with subject matter experts to identify relevant data insights and refine analytical approaches. Additionally, the Data Scientist will lead data discovery, ingestion, and governance initiatives across the J7 to establish a unified, secure, and accessible data ecosystem.

Requirements

• Bachelor’s degree and two (2)+ years of experience; additional four years of experience considered in lieu of degree.
• Experience in data science and/or analytics roles.
• Strong proficiency in programming languages such as Python, JavaScript, and SQL.
• Extensive experience with data visualization tools like Tableau, Power BI, or similar platforms.
• Strong knowledge and practical experience with statistical techniques, machine learning, and data science methodologies.
• Strong engineering background with knowledge of software architecture and software engineering principles.
• Knowledge of Agile software development practices.
• Familiarity with cloud platforms, especially Microsoft Azure.
• Experience working with containerized applications.
• Proficiency in Microsoft Office Suite (Word, Excel, PowerPoint, Outlook).
• High level of discretion and confidentiality in handling sensitive information.
• Must have an active Secret clearance with the ability to obtain a TSSCI.
• Must have Current US Citizenship.

Nice To Haves

• Experience with Department of Defense (DoD) software and systems.
• Strong analytical and problem-solving skills for implementing process improvements.

Responsibilities

• Represent J7 Directorate interests in high-level battle rhythm forums, aligning strategic objectives with command-wide priorities.
• Lead the integration of AI within the Joint Exercise Program, modernizing training methodologies and readiness.
• Orchestrate J7 data science initiatives from conception to delivery, aligning technical development teams with leadership priorities to ensure the on-time deployment of mission-critical data solutions.
• Develop and deploy predictive models, algorithms, and real-time support systems for operations, enhancing efficiency and providing actionable insights.
• Collaborate with cross-functional teams to identify data-driven opportunities, conduct research, apply emerging technologies, and optimize dashboards for stakeholder communications.
• Architect and maintain robust data models and schemas, ensuring the reliability and scalability of enterprise-level data pipelines.
• Collaborate with subject matter experts to identify relevant data insights and refine analytical approaches.
• Lead data discovery, ingestion, and governance initiatives across the J7 to establish a unified, secure, and accessible data ecosystem.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level