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Data Processor Jobs in Virginia Beach, VA (NOW HIRING)

The Coin Processor - Warehouse Role: In branch locations around the world, we're doing the critical ... Data Entry skills * Money handling experience * Customer Service experience * Ability to work ...

As a data scientist at Booz Allen, you can help turn these complex data sets into useful ... Identity Statement As part of the hiring process, we will ask you to complete an identity ...

Data Scientist

Hampton, VA · On-site

$99K - $225K/yr

As a data scientist at Booz Allen, you can help turn these complex data sets into useful ... Identity Statement As part of the hiring process, we will ask you to complete an identity ...

The Data Scientist will focus on performing ETL / data cleaning, developing interactive ... Experience developing in Palantir Foundry * RPA or general automation experience in UiPath or ...

The Data Scientist will focus on performing ETL / data cleaning, developing interactive ... Experience developing in Palantir Foundry * RPA or general automation experience in UiPath or ...

Showing results 21-40

Data Processor information

See Virginia Beach, VA salary details

$10

$17

$30

How much do data processor jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for data processor in Virginia Beach, VA is $17.92, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $19.76 per hour, depending on experience, location, and employer.

What is the difference between Data Processor vs Data Entry Clerk?

AspectData ProcessorData Entry Clerk
Required CredentialsHigh school diploma; some roles may require basic certificationsHigh school diploma; no specialized certifications typically needed
Work EnvironmentOffice settings, data centers, or remote workOffice environments, often in administrative settings
Employer & Industry UsageBusinesses, government agencies, financial institutionsCorporations, healthcare, retail, administrative offices
Common Search & ComparisonOften compared for data handling and processing tasksCompared for data input and administrative support roles

While both roles involve handling data, Data Processors typically perform more complex data management and validation tasks, often requiring some technical skills. Data Entry Clerks focus on inputting data accurately and efficiently. Understanding these differences helps in choosing the right role based on skills and career goals.

What are some common challenges faced by data processors and how can they be addressed?

Data Processors often encounter challenges such as managing large volumes of data accurately and efficiently, dealing with inconsistent or incomplete data, and ensuring data privacy and compliance. To address these, it's important to develop strong attention to detail, become proficient with data processing software, and stay updated on relevant data protection regulations. Collaborating closely with data analysts and IT teams can also help resolve data issues and improve workflow efficiency.

What is a data processor?

A data processor transfers, organizes, and processes personal data for a company. It is typically an entry-level job that serves as a starting point for a career as a data controller. As a data processor, your duties involve processing incoming documents, transferring analog documents into digital data, verifying the information in all documents, updating document formats, and creating detailed reports on company data use and management. Qualifications for this career include excellent computer skills and a bachelor’s degree in computer science or data management.

What are the key skills and qualifications needed to thrive as a data processor, and why are they important?

To thrive as a Data Processor, you need strong attention to detail, accuracy in data entry, and a high school diploma or equivalent. Familiarity with spreadsheet software (such as Microsoft Excel), database management systems, and sometimes data processing software is typically required. Excellent organizational skills, the ability to follow procedures, and effective time management make someone stand out in this role. These skills ensure data integrity, minimize errors, and support efficient information management within an organization.

How much does a data processor earn?

The average salary for a data processor in the United States ranges from $30,000 to $50,000 per year, depending on experience, location, and industry. Entry-level positions may start lower, while experienced data processors with specialized skills or certifications can earn higher wages. Salaries are often complemented by benefits such as health insurance and paid time off.

What do you do as a data processor?

A data processor collects, organizes, and manages data to ensure accuracy and accessibility. They often use software tools like spreadsheets or databases and may perform tasks such as data entry, validation, and updating to support business operations.
What job categories do people searching Data Processor jobs in Virginia Beach, VA look for? The top searched job categories for Data Processor jobs in Virginia Beach, VA are:
What cities near Virginia Beach, VA are hiring for Data Processor jobs? Cities near Virginia Beach, VA with the most Data Processor job openings:
Infographic showing various Data Processor job openings in Virginia Beach, VA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $37,268 per year, or $17.9 per hour.

Data Scientist / AI Engineer

Ironclad Defense Works

Norfolk, VA • On-site

$115 - $130/hr

Other

Medical, Dental, Retirement, PTO

Posted 4 days ago


Job description

Data Scientist / AI Engineer

Location: Norfolk, Virginia

Employment Type: Full-time, On-site

Security Clearance: Active NATO or U.S. National SECRET clearance required

Citizenship: Must be a citizen of a NATO member nation

The Role

Ironclad is seeking an experienced Data Scientist / AI Engineer to support the development and implementation of advanced data science, artificial intelligence, and large language model capabilities within the NATO enterprise.

This position requires a technically versatile professional who can bridge data engineering, software development, machine learning, and operational mission requirements. The selected candidate will design scalable data architectures, build and optimize data pipelines, develop API-based infrastructure, and support the secure deployment of AI and machine learning solutions in cloud-based and hybrid environments.

The role requires strong hands-on experience with generative AI, large language models (LLMs), distributed systems, microservices, containerized applications, and modern software engineering practices. The successful candidate must also be able to translate complex operational challenges into practical technical solutions for military and civilian stakeholders.

Key Responsibilities
  • Develop and implement scalable data science and AI capabilities supporting NATO initiatives.
  • Design, build, and maintain data pipelines for structured and unstructured data.
  • Prepare, cleanse, transform, and optimize data for LLM training, fine-tuning, inference, and analytics.
  • Develop API-based infrastructure that integrates LLMs and machine learning models with operational systems.
  • Design and support microservices and containerized AI/ML applications.
  • Build distributed data storage and processing solutions using cloud-based or hybrid architectures.
  • Develop real-time data processing and streaming capabilities for operational decision support.
  • Automate data engineering processes and improve the scalability, efficiency, and reliability of AI infrastructure.
  • Implement monitoring, logging, traceability, and performance-optimization tools for data pipelines and APIs.
  • Support the secure deployment of AI and LLM solutions in Microsoft Azure, AWS, or comparable environments.
  • Develop tools that improve data accessibility for data scientists, analysts, engineers, and operational users.
  • Collaborate with data scientists, software engineers, system architects, and other technical stakeholders.
  • Support federated learning, cross-domain data sharing, and secure collaboration across NATO nations.
  • Develop proofs of concept for LLM-based and advanced analytics applications.
  • Evaluate operational requirements and recommend appropriate AI, software, and data-engineering solutions.
  • Create dashboards, reports, and visual analytics for senior and non-technical stakeholders.
  • Provide technical briefings, mentoring, and training in AI engineering, data science, API development, and digital literacy.
  • Research emerging developments in generative AI, distributed computing, data architecture, and software engineering.
  • Promote responsible, secure, and ethical AI practices throughout solution development and deployment.
Required Qualifications
  • Bachelor’s degree or higher from a nationally recognized university in data science, data analytics, artificial intelligence, mathematics, physics, computer science, software engineering, or a closely related discipline.
  • At least four years of professional experience as a Data Scientist, Machine Learning Engineer, Data Engineer, Software Engineer, or in a closely related role.
  • Demonstrated experience developing operational AI or machine learning solutions.
  • Experience with distributed systems and cloud-based or hybrid architectures.
  • Experience designing API-based infrastructure and microservices architectures.
  • Hands‑on experience developing and deploying containerized applications using technologies such as Docker or Kubernetes.
  • Demonstrated experience with generative AI and large language models.
  • Experience preprocessing data and supporting the fine‑tuning and deployment of LLMs in secure, scalable environments.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, scikit‑learn, or comparable technologies.
  • Strong programming experience with Python, Java, Scala, or similar languages.
  • Experience with version control, CI/CD pipelines, automated testing, and modern software engineering practices.
  • Experience building and optimizing ETL processes, data pipelines, and real‑time streaming solutions.
  • Familiarity with Apache Airflow, Kafka, Spark, or comparable data‑engineering technologies.
  • Experience architecting or maintaining data lakes, data warehouses, distributed storage systems, or NoSQL solutions.
  • Knowledge of platforms such as Delta Lake, Snowflake, Hadoop, or comparable technologies.
  • Experience applying AI to operational decision support and the analysis of unstructured data, including text or imagery.
  • Strong understanding of data security, privacy, sovereignty, and responsible AI practices.
  • Experience developing dashboards, visual reports, and analytics using Tableau, Microsoft Power BI, Kibana, or comparable tools.
  • Ability to translate operational problems into practical AI and machine learning solutions.
  • Demonstrated success working with multidisciplinary technical teams.
  • Strong written and verbal communication skills.
  • Ability to explain technical concepts to non‑technical stakeholders and senior leaders.
  • Ability to mentor or train personnel in AI engineering, data science, or software development concepts.
Preferred Qualifications
  • Familiarity with NATO processes, organizational structures, operational culture, and decision‑making procedures.
  • Experience supporting military, defense, government, or international organizations.
  • Experience developing AI or data‑engineering solutions using open‑source frameworks and publicly available datasets.
  • Familiarity with military staff workflows and operational planning processes.
  • Experience with federated learning and privacy‑preserving collaboration across multiple organizations or nations.
  • Experience supporting cross‑domain data sharing and API‑driven interoperability.
  • Familiarity with agile project‑management methods and tools such as JIRA, Trello, or Microsoft Loop.
  • Experience briefing senior leaders and presenting actionable, data‑driven recommendations.
  • Knowledge of ethical AI principles, including bias mitigation, responsible data handling, transparency, and secure deployment.
Why Join Ironclad

Ironclad supports complex defense and international missions by providing experienced professionals who combine technical expertise with an understanding of operational requirements. This position offers the opportunity to contribute directly to secure, scalable, and mission‑focused AI capabilities while working alongside military, civilian, and technical stakeholders across the NATO enterprise.

Clearance

This position requires anactive NATO or National SECRET (or higher) security clearance. Applicants who do not possess the clearance specified above cannot be considered at this time.

Compensation

Compensation for this position ranges from $115,000 - $130,000 annually. Final salary will be based on factors such as experience, education, skills, qualifications, contract requirements, and overall affordability.

Eligible full‑time employees may also receive a comprehensive benefits package, including medical and dental insurance, retirement benefits, paid leave, and professional development opportunities.

Ironclad Defense Works is an Equal Opportunity Employer.

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