Data Scientist

Summary

MANTECH International Corporation is a technology and national security solutions provider serving government intelligence, defense, and federal civilian sectors. The Data Scientist will develop and maintain production machine learning and natural language processing models, modernize data products and pipelines, and translate policy and program questions into actionable analysis. The role also contributes to Azure-based cloud solutions and strengthens internal data-science capabilities through collaboration and reusable tooling.

Responsibilities

• 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

Skills

• 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
• 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
• 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

Qualifications

Must Haves

• 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
• 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

Nice to Haves

• 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

Benefits

• Health Insurance, dependent upon position
• Life Insurance, dependent upon position
• Paid Time Off, dependent upon position
• Holiday Pay, dependent upon position
• Short-term and long-term Disability, dependent upon position
• Retirement and Savings, dependent upon position
• Learning and Development opportunities, dependent upon position
• Wellness programs, dependent upon position
• Other optional benefit elections, dependent upon position