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3 results for Data Scientist in Washington, DC

Data Engineer

Arlington, VA
onsite
Permanent / Full Time
150000 - 170000 USD / Yearly
We are looking for an experienced Data Engineer for a full time opportunity in Northern, Virginia. In this role, you will design reliable data solutions that support analytics and business decision-making while helping improve the overall data environment. The ideal candidate brings strong technical depth in modern data engineering practices and enjoys building scalable systems from the ground up. Responsibilities:• Design, develop, and maintain robust data pipelines that collect, transform, and deliver high-quality data for reporting and analysis.• Create and optimize data models that support business intelligence, analytics, and operational use cases across the organization.• Build and manage ETL workflows using Python and related technologies to ensure efficient movement of data between systems.• Work with large-scale data processing tools such as Apache Spark and Hadoop to handle complex and high-volume datasets.• Integrate streaming and batch data sources using technologies such as Apache Kafka to support timely and reliable data availability.• Collaborate with analysts, engineers, and business stakeholders to translate data needs into scalable engineering solutions.• Improve data warehouse performance, structure, and reliability to support accurate and accessible enterprise data.• Use dbt and other modern data transformation practices to organize, test, and document datasets effectively.
2026-08-26T00:00:00Z

Machine Learning Engineer

Herndon, VA
remote
Temporary / Contract
70 - 75 USD / Hourly
Machine Learning EngineerPay: $70-75/hr, available solely on W2 BasisConsultant I (Contractor)Work Location: RemoteEngagement Type: 34 Week Contract, Potential for Extension or ConversionPosition OverviewWe are seeking a Machine Learning Engineer to support the design, development, and optimization of machine learning solutions for real‑world applications. This role focuses on model development, data pipeline construction, and performance evaluation within a collaborative engineering environment.Key Responsibilities<ul><li>Design, build, train, and evaluate machine learning and deep learning models for production and analytical use cases</li><li>Develop and maintain scalable data pipelines for data collection, cleaning, transformation, and ingestion</li><li>Conduct experiments and analyze performance metrics such as accuracy, recall, and AUC</li><li>Optimize models for performance, speed, reliability, and scalability</li><li>Collaborate with cross‑functional teams to support data‑driven solutions</li></ul>
2026-09-03T00:00:00Z

Business Intelligence (BI) Engineer

Herndon, VA
onsite
Permanent / Full Time
100000 - 125000 USD / Yearly
We are looking for an experienced Business Intelligence Engineer to lead and elevate our enterprise analytics environment in Reston, Virginia. This role is ideal for a hands-on technical expert who can shape data strategy, deliver trusted reporting, and partner with senior stakeholders to turn complex information into clear business direction. You will influence how analytics are governed, prioritized, and scaled while helping expand the use of AI-driven solutions across reporting and decision support. Responsibilities: • Lead the design, development, and ongoing optimization of the organization’s analytics ecosystem across cloud data platforms, reporting solutions, and integrated data services. • Build and maintain reliable data pipelines, structured data models, and system integrations that support accurate, scalable, and timely business intelligence delivery. • Create and enhance Power BI dashboards and semantic models, with attention to usability, performance, security, and content governance. • Partner with executive, finance, operations, and clinical leadership to define meaningful KPIs, refine business questions, and translate analytical needs into actionable solutions. • Establish practical standards for data governance, documentation, prioritization, and delivery to ensure analytics work is consistent, transparent, and sustainable. • Design and implement AI-enabled analytics tools such as natural-language query experiences, retrieval-based applications, or agent-driven workflows that improve access to insights. • Evaluate AI solutions for safety, reliability, accuracy, and cost efficiency, and apply appropriate controls to support responsible adoption. • Serve as the senior technical owner for analytics initiatives, working independently while coordinating with contractors or external partners when specialized support is needed.
2026-09-01T00:00:00Z