We are seeking a Data Scientist - Enterprise Data and AI Solutions to join our Hyperautomation team. This role is designed for an analytically curious, technically versatile data scientist who can discover, correlate, enrich, and operationalize enterprise data in support of complex business, operational, security, and modernization use cases.

The successful candidate will work across enterprise platforms such as Splunk, ServiceNow, Databricks, and related data and automation tools to identify where relevant data resides, evaluate its reliability, reconcile conflicting records, and translate findings into repeatable analytics, AI-enabled enrichment capabilities, dashboards, pipelines, and automated workflows.

This position goes beyond predefined reporting. It requires someone who can start with an ambiguous objective, investigate multiple systems, determine what data can and cannot support, and apply data science, analytics, artificial intelligence, machine learning concepts, and automation to produce defensible and scalable solutions.

This role is hybrid and reports onsite in Washington, DC at least 1 day a week and as required for meetings, testing or other gov activities as directed by their lead.

Key Responsibilities:

Data Discovery and Analytics: Lead investigative data-discovery and analytics efforts when the required data source, field, or solution path is not yet defined.
Enterprise Platform Analysis: Investigate Splunk, ServiceNow, Databricks, and other enterprise data sources to identify relevant indexes, sourcetypes, tables, APIs, fields, relationships, and authoritative records.
Data Correlation and Reconciliation: Identify correlation keys across configuration management, endpoint, identity, asset, application, security, and operational datasets; reconcile incomplete, inconsistent, duplicated, or conflicting records.
Advanced Querying and Scripting: Develop and optimize searches, queries, scripts, and analytical workflows using SPL, SQL, Python, REST APIs, JSON, and structured or semi-structured data.
AI-Enabled Data Enrichment: Use approved artificial intelligence and generative AI capabilities, including prompt-based APIs, to classify, normalize, extract, infer, and generate missing data points from available record-level context.
AI Output Validation: Evaluate generated or inferred data for accuracy, consistency, business usability, and traceability before incorporating it into analytics, reporting, or operational processes.
Automation Integration: Partner with data engineering, robotic process automation, Power Automate, and workflow teams to convert discoveries and enrichment processes into repeatable, governed, and sustainable enterprise capabilities.
Communication and Prototyping: Develop prototypes, dashboards, proofs of concept, and visualizations; communicate findings, assumptions, risks, data limitations, and recommendations to technical teams and leadership.

SAIC® is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

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