Data Scientist

MANTECH; Arlington (VA); Hybrid; USD 110,000 - 150,000; Full time

Job summary

MANTECH International Corporation seeks a Data Scientist to join its Arlington, VA team in a hybrid role with on-site days each month. You will develop, deploy, and maintain production ML and NLP models using large human-capital data, while modernizing data products and pipelines on an Azure-first platform.

The role requires 2–3 years of hands-on ML/NLP experience, a quantitative bachelor’s degree, and strong Python skills. Collaboration across Agile teams and stakeholders is essential.

Qualifications

• Bachelor’s degree in a quantitative field as listed.
• Experience building production ML and NLP models.
• Strong Python skills for data pipelines and automation.
• Familiar with Agile teams and collaborative tooling.

Responsibilities

• Develop, deploy, and maintain production ML and NLP models with large datasets.
• Build data products and pipelines across legacy and cloud systems.
• Translate policy questions into scoped analytical work for stakeholders.
• Contribute to a cloud-first Azure stack with security and governance.
• Mentor others and promote reusable tooling in the team.

Skills

Python programming

NLP/ML modeling

Data analysis

Agile teamwork

Education

Bachelor’s degree in mathematics, statistics, computer science, engineering, data science, or related field

Tools

VS Code

Git

GitHub Copilot

Azure Databricks

Azure OpenAI

Azure AI Search

Job description

MANTECH International Corporation seeks a motivated, career and customer-oriented Data Scientist to join our team in Arlington, VA. This is a hybrid position with several days onsite per month as needed.
You’ll support a U.S. federal civilian agency that serves as the central authority on human capital across the federal workforce, helping advance strategic goals around modernizing its use of data, building a stronger analytics workforce across government, delivering trusted human-capital data products to agencies and employees, and strengthening data governance, privacy, and security.
Responsibilities Include But Are Not Limited To

• Develop, deploy, and maintain production ML and NLP models that surface insights from large volumes of human-capital and workforce data, directly supporting decisions made by federal agencies, employees, and the public.
• Build and modernize data products and pipelines that improve data access, integration, and quality across legacy and cloud-based systems.
• Translate ambiguous policy and program questions into well-scoped analytical work, partnering with non-technical stakeholders and presenting results in ways decision-makers can act on.
• Contribute to a modern, cloud-first technology stack (Azure ecosystem) that meets federal standards for security, privacy, and governance.
• Help strengthen the client's internal data-science capability through pairing, code review, knowledge transfer, and reusable tooling.
  

Minimum Qualifications

• 2–3 years of experience developing, deploying, and maintaining large-scale ML models in production using real‑world data
• Bachelor’s degree in mathematics, statistics, computer science, engineering, data science, or a related quantitative field
• Hands-on experience building and evaluating NLP-based machine learning models
• Strong Python skills for developing and automating ML models and data pipelines
• Proficiency with collaborative development tools (VS Code, Git, GitHub Copilot)
• Experience working in Agile teams to iteratively develop and deliver data products
• Strong analytical, communication, and cross-functional collaboration skills, including translating ambiguous requirements into actionable solutions
  

Preferred Qualifications

• Experience using Azure cloud products such as Azure Databricks, Azure DevOps, Azure OpenAI, and Azure AI Search.
• Experience delivering data-science work in a federal or other regulated environment, with awareness of FedRAMP, FISMA, or similar compliance regimes.
• Experience working with human-capital, workforce, survey, or other administrative-record data.
• Experience with MLOps tooling and patterns for monitoring, retraining, and governing models in production.
  

Clearance Requirements

• This role requires the ability to obtain and maintain a U.S. Public Trust clearance. U.S. citizenship or other status meeting the federal investigative requirements is required at the time of hire.