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Leads AI and data consulting workstreams focused on fraud detection, payment integrity, and improper-payment analytics. Designs and deploys scalable machine learning models, analytics workflows, and fraud rules; partners with clients to identify use cases; presents deliverables to executives; mentors junior consultants; and ensures governance, security, and responsible AI compliance.

Leads enterprise data architecture for a secure Databricks lakehouse, including Unity Catalog governance, canonical HR data models, DataOps, ingestion, orchestration, APIs, migration, metadata, lineage, quality, and data-product standards. Serves as deputy data workstream lead, guides architecture decisions, reviews technical deliverables, communicates tradeoffs, mentors architects and engineers, and provides technical quality assurance.

Design, build, and operate scalable cloud-native data pipelines and data lake/fabric architectures for Revenue Cycle Management. Implement ETL/ELT, integrate structured and unstructured sources and APIs, ensure data quality, lineage, and governance, and support AI/ML and analytics workloads with CI/CD and DevOps practices.

Leads enterprise data migration and modernization programs, including strategy, governance, system rationalization, migration wave prioritization, data quality, Databricks execution, testing, stabilization, and operational transition. Coordinates multidisciplinary stakeholders, advises executives, manages delivery roadmaps and resource models, and establishes repeatable standards, metrics, decision gates, and rollout processes.

Lead planning, execution, and delivery of technical projects across data, analytics, and system implementation. Coordinate stakeholders and technical teams, define scope, timelines, budgets and resources, run Agile ceremonies, track risks/issues, translate business needs into technical tasks, provide executive status updates, ensure governance and quality, and support change management and user adoption.

Perform advanced fraud and cybersecurity analytics: analyze large structured and unstructured datasets, develop and test detection logic and predictive models, conduct investigative/forensic analysis, support ETL and data quality, create dashboards and reports, collaborate with stakeholders, and participate in incident response. Work onsite at client location in Lanham, MD.

Perform fraud analytics and investigative support: analyze transaction and log data to identify anomalies and trends, support detection logic and ETL/data quality, produce reports and dashboards, assist forensic and investigative activities, document methodologies, and collaborate with stakeholders. Work onsite in Lanham, MD full time and maintain required clearance.

Guidehouse is seeking a Data Scientist to collect and analyze data, develop visualizations, ensure data governance, and support decision-making for large-scale programs within DHS.

Support fraud analytics operations by performing data review, cleanup, basic analysis, documentation, reporting, and project support. Prepare meeting notes, trackers, briefings, and follow established procedures while coordinating with team members to ensure timely delivery.

Supports federal financial management modernization by assessing systems and processes, documenting inventories and data flows, analyzing total costs and capability gaps, developing requirements and roadmaps, preparing governance materials, tracking risks and metrics, and creating procedures, training, and knowledge-transfer documentation.