Top Senior Data Science Jobs in Washington, DC

Leads advanced data science and analytics initiatives using statistics, modeling, machine learning, and business analysis. Develops scalable policy-adherence metrics and valuation models using complex structured and unstructured healthcare data, including claims and denials. Creates reports, projections, and presentations; advises executives; manages stakeholders; and influences roadmap and implementation decisions across compliance, contracting, Medicaid, and business teams.

Design, test, and implement supervised and unsupervised statistical and ML models to detect loan fraud and improper payments. Support criminal investigations with data analysis, develop repeatable data pipelines, document methods for evidentiary use, and build visualizations and dashboards. Collaborate with investigators, data engineers, and leadership; automate tasks with Python and Office/Power Platform tools; and identify new analytic opportunities.

Design, implement, and scale NLP and ML solutions to detect loan fraud and improper payments. Clean and analyze large unstructured corpora, build supervised and unsupervised models, support criminal investigations, document methodology to meet evidentiary standards, produce dashboards and reports, and coordinate with data engineering for production pipelines.

Design and implement ML and predictive analytics solutions on multi-INT datasets. Retrieve, merge, and analyze structured and unstructured data, build AI/ML tools, and produce visual and written analytic products for defense customers. Support database administration, data engineering, and deliverables in a classified, mission-driven environment.

Design and implement data pipelines and predictive models using SAP and non‑SAP data. Clean and validate large ERP datasets, perform statistical and exploratory analyses, build ML/AI solutions (SAP Analytics Cloud or external platforms), and produce dashboards and KPIs. Collaborate with IT and stakeholders to deploy data‑driven solutions and justify model value.

Lead data science for defense clients: perform data engineering, mining, exploratory/predictive/statistical analysis; build ML/AI tools (recommendation engines, automated scoring); manage large, disparate data sources using R/Python/SQL; create visualizations in Power BI/Tableau; support Multi-INT analytics and provide senior-level analytic products for the defense cover program.

The Senior Database Architect analyzes and designs data solutions for enterprise reporting and operational decision-making, collaborating with various technical teams.

Lead development of NLP and ML solutions for large-scale legal, news, financial, and business corpora. Build, train, evaluate, and deploy traditional and deep learning models (including LLMs), design scalable pipelines, evaluate SOTA tools, partner with product and engineering teams, and mentor junior staff while contributing to model monitoring and production best practices.

Leads advanced analytics and data science initiatives supporting federal communications, outreach, stakeholder engagement, and mission performance. Develops predictive models, forecasts, anomaly detection, dashboards, reporting frameworks, and measurement methodologies. Translates complex data into leadership recommendations, supports data pipelines and workflow automation, ensures governance and quality, and mentors team members. Collaborates with communications, UX, technology, and governance stakeholders while implementing machine learning and generative AI solutions in cloud environments.

Lead design and implementation of Palantir Foundry–based data collection and analytics for USAF Mission Assurance. Design user interfaces, build and scale AI/ML models and data workflows, integrate with DoD/AF systems, produce decision-relevant analytics, maintain platforms, and provide documentation and training.

Lead large-scale, cross-functional data science initiatives from ambiguous problem definitions to production. Orchestrate multi-team efforts, set timelines, implement MLOps pipelines, define processes and best practices, mentor senior data scientists, and advise executive leadership on technical strategy.

Lead technical AI work to fine-tune, evaluate, and scale LLMs and ML pipelines for semantic metadata, recommendation and personalization systems. Build production-grade ASR, vector search, and BigQuery-based analytics; ensure model accuracy, ethical guardrails, bias mitigation, and secure cloud deployments while collaborating with cross-functional teams.

Seeking a Senior Data Scientist to design, code, and improve models and algorithms, evaluate decision systems, and partner with teams to translate data into impactful behaviors.

Lead Data Scientist will support advanced analytics, predictive modeling, and machine learning initiatives for clinical decision-making in healthcare. Responsibilities include algorithm design and compliance with VA governance standards.

Lead design and execution of claims-based RWE and HEOR analyses using Medicare/Medicaid/commercial data. Develop and validate SAS programs, build reproducible analytic pipelines, synthesize findings for payer strategy and policy, mentor junior staff, and support client-ready deliverables and proposals.

Lead end-to-end data science work: exploratory and statistical analysis, data engineering, ML model development (recommendation engines, predictive systems), data visualization (Power BI, Tableau), and multi-int large-data analytics to support defense programs and produce actionable intelligence products.

Activate and operationalize clinical data for analytics by designing data models, taxonomies, and a clinical feature store; build reusable data assets, documentation, and dashboards; ensure data quality and compliance; partner with stakeholders and data engineering to enable downstream analysts, data scientists, and business users.

Lead analyst at the Pentagon overseeing a distributed analytics team to standardize, extract, validate, and analyze DoD logistics data. Build automation, predictive models, visualizations, and reports using Python/R/SQL and ML frameworks. Use high-resolution simulation tools and DoD logistics systems to support operational decision-making and mission readiness.

Lead analysis of large datasets using Databricks to identify trends, model customer retention/churn, create visualizations and dashboards, and integrate AI-driven solutions to support decision-making for consumer and retail analytics.