Enterprise Data and AI Solutions Scientist

SAIC • Washington, DC

11h • Hybrid

About The Position

We are seeking an Enterprise Data and AI Solutions Scientist to join our Hyperautomation team. This role is designed for an analytically curious and technically versatile “data hunter” who thrives when the required data source, system, field, or solution has not yet been identified. The successful candidate will lead investigative data-discovery efforts across enterprise platforms, determine where relevant information resides, evaluate its reliability, correlate records across disparate systems, and translate findings into repeatable analytics, AI-enabled data-enrichment capabilities, and automated workflows. This position goes beyond querying known datasets or producing predefined reports. It requires someone who can take an ambiguous business objective, investigate multiple enterprise systems, identify relationships among incomplete or conflicting datasets, and develop an evidence-based approach to solving the problem. This individual will bridge the gap between raw enterprise data, intelligent data enrichment, and automation.

Requirements

• Investigative Curiosity: A persistent drive to explore unfamiliar systems and data structures until a defensible answer or path forward is identified.
• Systems Thinking: The ability to understand how data flows across applications, infrastructure, identity systems, assets, and business processes.
• Evidence-Based Discipline: A rigorous approach to validating conclusions, documenting data lineage, and distinguishing authoritative, derived, and AI-generated information.
• Solution Orientation: The ability to turn one-time discoveries into reusable, scalable, and supportable enterprise capabilities.
• Consultative Communication: The ability to translate complex data findings into clear, actionable recommendations for technical and business stakeholders.
• Comfortable beginning with an unanswered question, navigating unfamiliar enterprise systems, testing hypotheses, and synthesizing findings into actionable insights.

Nice To Haves

• Experience with Splunk and ServiceNow platforms.
• Proficiency in SPL, SQL, Python, and REST APIs.
• Experience with AI and Generative AI capabilities.
• Familiarity with RPA and workflow automation tools.
• Experience with Databricks, Power Automate.

Responsibilities

• Lead data-hunting and investigative analytics efforts in support of complex business, operational, security, and hyperautomation use cases.
• Investigate enterprise platforms, particularly Splunk and ServiceNow, to identify relevant indexes, sourcetypes, tables, fields, APIs, relationships, and authoritative data sources.
• Identify correlation keys across disparate systems, including configuration-management, endpoint, identity, asset, and operational data. Develop methods for reconciling incomplete, inconsistent, duplicated, or conflicting records.
• Develop and optimize searches, queries, scripts, and analytical workflows using SPL, SQL, Python, REST APIs, and related data-retrieval technologies.
• Use approved AI and Generative AI capabilities, including prompt-based APIs, to normalize data, extract attributes, and generate missing data points from available record-level context. Examples may include using known IT asset manufacturers and models to determine or infer lifecycle attributes such as End of Life or End of Support.
• Evaluate AI-generated attributes for accuracy, consistency, and business usability. Clearly distinguish authoritative source data from inferred or generated information and document supporting evidence, confidence, and known limitations.
• Partner with RPA, workflow, and data-engineering teams to convert successful analytical discoveries and enrichment processes into repeatable, governed, and sustainable enterprise capabilities.
• Help determine whether a use case is best addressed through data engineering, API integration, business-process automation, robotic process automation, AI-enabled enrichment, or a hybrid approach.
• Develop prototypes, proofs of concept, dashboards, and visualizations. Communicate findings, data limitations, technical risks, and recommendations to both technical teams and senior leadership.

Benefits

• This role allows some remote work.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed