Ai Data Annotation Jobs in Virginia (NOW HIRING)

Senior Data & AI Analytics Lead
Position Overview THIS IS A MOSTLY REMOTE ROLE WITH OCASSIONAL TRAVEL TO MCLEAN AND FORT BELVOIR We are seeking a senior-level data and analytics professional to lead complex AI, machine learning, and advanced analytics initiatives from concept through deployment. This individual will oversee multidisciplinary teams, guide technical strategy, and collaborate with stakeholders to transform large and diverse datasets into actionable business intelligence and operational improvements. Key Responsibilities
Direct the planning, execution, and delivery of data science, machine learning, and AI-focused initiatives while managing project scope, risks, timelines, and outcomes.
Facilitate discovery sessions, strategic workshops, and collaborative solution-design engagements with business and technical stakeholders to identify opportunities and define analytical approaches.
Lead efforts to identify, acquire, integrate, and prepare data from a variety of structured and unstructured sources.
Oversee data ingestion, transformation, and enrichment processes, including ETL/ELT workflows and data annotation activities supporting advanced analytics use cases.
Guide development teams through the full machine learning lifecycle, including data preparation, feature engineering, model development, testing, validation, implementation, and performance monitoring.
Translate analytical findings into business recommendations and communicate complex technical concepts to executive and non-technical audiences.
Manage multiple workstreams simultaneously while ensuring high-quality delivery, operational efficiency, and stakeholder alignment.
Establish and track performance indicators, operational metrics, dashboards, and reporting capabilities to support data-driven decision making.
Drive continuous enhancement of analytics platforms, reporting environments, and data science best practices.
Mentor data scientists, engineers, and analytical professionals while fostering innovation and technical excellence. Required Qualifications
Highly preferred GCP expertise and/or certifications
Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related technical discipline. Advanced degrees are highly desirable.
5+ years of leadership experience directing teams of data scientists, engineers, and analytics professionals across multiple projects or initiatives.
Demonstrated expertise in machine learning, natural language processing, information retrieval, or advanced analytics involving large-scale unstructured datasets.
Strong understanding of the complete data science lifecycle, including data acquisition, cleansing, feature development, model selection, validation, deployment, and production support.
Experience developing AI and machine learning solutions using object-oriented programming principles and software engineering best practices.
Ability to optimize, refactor, and enhance code performance, maintainability, and scalability.
Hands-on experience with distributed computing and large-scale data processing environments utilizing technologies such as Spark, Hadoop ecosystem components, and parallel-processing architectures.
Familiarity with enterprise data platforms including NoSQL databases, data warehouses, and cloud-based analytics environments.
Experience working within one or more major cloud platforms and leveraging cloud-native analytics, machine learning, and data engineering services.
Proficiency developing and integrating web services and APIs, including REST-based architectures.
Working knowledge of modern front-end frameworks and web technologies used for data-driven applications and user interfaces.
Experience leveraging SQL and relational databases to query, transform, and analyze large and complex datasets.
Strong programming capabilities in Python, R, or comparable data science languages.
Familiarity with Linux-based environments, automation scripting, data structures, algorithms, and software development methodologies.
Ability to develop scalable, production-ready applications and analytical solutions.
Excellent analytical thinking, communication, and stakeholder engagement skills with a demonstrated ability to bridge technical and business audiences.
Proven ability to collaborate across functional teams and translate business objectives into technical solutions. Preferred Experience
Cloud-based data engineering and analytics implementations.
Development of enterprise-scale AI or machine learning solutions deployed to production environments.
Experience building operational dashboards, executive reporting solutions, and data visualization platforms.
Exposure to multimodal data sources including text, documents, images, audio, video, transactional, operational, or financial datasets.
Background working in fast-paced consulting, advisory, or large-scale transformation environments.