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Data Annotation Manager Jobs in Gaithersburg, MD

Beyond SOF

DATA ENGINEER

Reston, VA · On-site

$119K - $143K/yr

Designs, implements, and operates data management systems for intelligence needs Designs how data ... Java -JDK 1.6+, Model View Controller (MVC) architecture, Annotation, Servelet 2.5/Java Server ...

Seekr

Senior Data Scientist

Reston, VA · On-site

Manage machine learning algorithm lifecycle * Support pre-sales efforts, identifying how the Seekr Platform could help satisfy customer requirements * Coordinate data collection and annotation ...

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Data Annotation Manager information

See Gaithersburg, MD salary details

$33.5K

$105K

$185.8K

How much do data annotation manager jobs pay per year?

As of Aug 13, 2026, the average yearly pay for data annotation manager in Gaithersburg, MD is $104,960.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,300.00 and $135,600.00 per year, depending on experience, location, and employer.

What are some common challenges faced by data annotation managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a data annotation manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

What are the key skills and qualifications needed to thrive as a data annotation manager?

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Gaithersburg, MD? The most popular types of Data Annotation jobs in Gaithersburg, MD are:
What are popular job titles related to Data Annotation Manager jobs in Gaithersburg, MD? For Data Annotation Manager jobs in Gaithersburg, MD, the most frequently searched job titles are:
What job categories do people searching Data Annotation Manager jobs in Gaithersburg, MD look for? The top searched job categories for Data Annotation Manager jobs in Gaithersburg, MD are:
What cities near Gaithersburg, MD are hiring for Data Annotation Manager jobs? Cities near Gaithersburg, MD with the most Data Annotation Manager job openings:
Data Annotation Manager jobs near you

AI and Analytics Lead with Security Clearance

Kforce Federal Solutions

Tysons, VA • On-site

Other

Posted 27 days ago

Job description

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.

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