SAIC
Enterprise Data and AI Solutions Scientist
Washington, District of Columbia, USA · Senior · Full-time
No sponsorship$80k-$120kDetected 34 days ago
PythonData StructuresSQLDatabricksVector DatabasesRESTSparkData EngineeringData ScienceNLPLLMsRAGStatisticsSystems EngineeringCommunicationProblem Solving
About the role
- This position goes beyond querying known datasets or producing predefined reports.
- This individual will bridge the gap between raw enterprise data, intelligent data enrichment, and automation.
- What You Will Bring to the Team You are more than a reporting specialist or traditional data scientist.
Responsibilities
- Investigative Data Discovery: Lead data-hunting and investigative analytics efforts in support of complex business, operational, security, and hyperautomation use cases.
- Develop methods for reconciling 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, and related data-retrieval technologies.
- 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.
- Clearly distinguish authoritative source data from inferred or generated information and document supporting evidence, confidence, and known limitations.
- Automation Integration: Partner with RPA, workflow, and data-engineering teams to convert successful analytical discoveries and enrichment processes into repeatable, governed, and sustainable enterprise capabilities.
- Prototyping and Communication: Develop prototypes, proofs of concept, dashboards, and visualizations.
- Core Competencies: Investigative Curiosity: A persistent drive to explore unfamiliar systems and data structures until a defensible answer or path forward is identified.
- Sending known asset attributes, such as manufacturer, model, product family, and software version, to an approved AI service to generate missing lifecycle information, including estimated End-of-Life and End-of-Support dates.
Requirements
- Equivalent practical experience may be considered in lieu of a degree.
- Demonstrated experience conducting data discovery or investigative analytics when the required data sources, fields, or technical approach were not predefined.
- Hands-on Splunk experience, including SPL development, index and sourcetype discovery, field analysis, lookups, joins, and cross-source data correlation.
- Strong proficiency in SQL and Python for data retrieval, manipulation, integration, and analysis.
- Experience working with REST APIs, JSON, and structured or semi-structured data.
- Practical experience using AI, Generative AI, or prompt-based services to extract, classify, normalize, infer, or enrich enterprise data.
- Experience evaluating and validating generated or inferred data before incorporating it into analytics, reporting, or operational processes.
- Ability to work independently in ambiguous environments, formulate and test hypotheses, and adapt based on emerging findings.
- Required Clearance: ship.
- 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.
Nice to have
- Experience with Databricks, Apache Spark, Delta Lake, or cloud-based lakehouse architectures.
- Experience operationalizing AI-generated or AI-enriched data through automated pipelines, dashboards, workflow tools, or human-in-the-loop review processes.
- Familiarity with Retrieval-Augmented Generation, semantic matching, embedding models, vector databases, entity resolution, or related information-retrieval techniques.
- Experience working in federal government, regulated-industry, cybersecurity, IT asset-management, or large-scale enterprise environments.
- SAIC is Redefining Ingenuity through its deep customer and domain knowledge to enable the delivery of systems engineering and integration offerings for large, complex projects.
- For more information, visit saic.com.
Compensation
- $80,001 - $120,000.
- The estimate displayed represents the typical salary range for this position based on experience and other factors. <![CDATA[SAIC is a premier technology integrator providing full life cycle services and solutions in the technical, engineering, intelligence, and enterprise information technology markets.
- SAIC's approximately 15,000 employees are driven by integrity and mission focus to serve customers in the U.S. federal government.
- Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $4.5 billion.
Benefits
- For information on the benefits SAIC offers, see.
This listing is sourced directly from SAIC's careers page and normalized into a canonical job model.