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Data Scientist

Venatore LLC

Fort Belvoir · On-site Full-time 1w ago

About the role

About

The following position(s) are contingent upon the award of a contract with our government customer. We welcome candidates interested in prime or subcontractor alignment.

The Artificial Intelligence Integrator supports Westover Air Reserve Base by delivering full-time, on-site artificial intelligence, machine learning, and automation expertise for Base Civil Engineering operations. This position is based in Chicopee, Massachusetts and requires on-site support. The role leads the design, development, testing, training, deployment, and sustainment of custom AI solutions that improve operational efficiency, strengthen mission readiness, and support long-term modernization goals. The successful candidate will work directly with government personnel to develop mission-focused solutions in contract analysis, energy optimization, and snowfall recovery, while managing the full lifecycle of AI integration from data preparation through deployment, training, and continuous improvement.

Responsibilities

Artificial Intelligence Solution Development

  • Design, train, validate, optimize, and deploy artificial intelligence and machine learning models addressing Base Civil Engineering mission needs.
  • Develop and enhance solutions for contract and revision analysis, energy monitoring and optimization, and snowfall recovery and readiness.
  • Transition pilot and beta capabilities into reliable operational tools for government users.
  • Apply predictive modeling, statistical analysis, and automation to extract actionable insights from structured and unstructured data.
  • Define model performance metrics, operational benchmarks, and improvement plans aligned with mission requirements.

Data Engineering and Model Operations

  • Collect, prepare, cleanse, label, and validate data from multiple government-owned sources.
  • Build scalable data pipelines, feature engineering workflows, and repeatable model training processes.
  • Analyze historical and real-time data to identify trends, inefficiencies, and operational risks.
  • Perform model retraining, tuning, benchmarking, and performance monitoring.
  • Maintain traceability between data sources, model outputs, and operational use cases.

Secure System Integration and Deployment

  • Integrate AI solutions into secure, local, and air-gapped environments in accordance with government requirements.
  • Support development, test, and production environments within approved security boundaries.
  • Implement secure coding practices and cybersecurity controls to protect Controlled Unclassified Information and Federal Contract Information.
  • Ensure alignment with security standards, AI ethical principles, and compliance requirements.
  • Coordinate system updates, upgrades, and changes with government stakeholders and IT personnel.

Documentation, Training, and Sustainment

  • Develop and maintain system documentation, user guides, technical manuals, and operational materials.
  • Conduct recurring monthly training for Air Force personnel on AI tools and workflows.
  • Prepare and deliver monthly status reports covering progress, risks, and performance.
  • Support patching, bug fixes, model updates, and sustainment activities.
  • Deliver briefings, demonstrations, and written updates to leadership and stakeholders.

Collaboration and Mission Support

  • Collaborate with government leads, users, and support teams to align solutions with mission objectives.
  • Participate in meetings, working groups, and technical discussions as required.
  • Coordinate testing, validation, and release activities.
  • Identify process gaps, data limitations, and integration risks, and recommend improvements.
  • Maintain professional accountability in an on-site, mission-focused environment.

Required Qualifications

  • Demonstrated experience designing, building, testing, and deploying artificial intelligence or machine learning solutions in operational environments.
  • Hands‑on experience with machine learning frameworks such as TensorFlow, PyTorch, scikit‑learn, Keras, or similar tools.
  • Strong programming skills in Python and experience in Linux‑based environments.
  • Experience with data preparation, labeling, feature engineering, ETL processes, and model validation.
  • Familiarity with secure software engineering practices, APIs, containerization, and modern deployment approaches.
  • Working knowledge of cybersecurity practices, including protection of Controlled Unclassified Information and Federal Contract Information.
  • Experience producing technical documentation, training materials, and briefings for varied audiences.
  • Ability to work full‑time on‑site at Westover Air Reserve Base in Chicopee, Massachusetts.
  • Ability to operate effectively in a structured government environment.
  • Strong communication, collaboration, and problem‑solving skills.

Preferred Qualifications

  • Experience supporting Department of Defense, Department of the Air Force, or Air Force Reserve environments.
  • Experience integrating AI solutions in secure, local, hybrid, or cloud‑informed environments (e.g., AWS GovCloud, Azure IL5/IL6 concepts).
  • Experience with Docker, Kubernetes, DevSecOps pipelines, version control, and automation tools.
  • Experience with backend frameworks and data platforms such as Django, Celery, PostgreSQL, Apache Spark, or Databricks.
  • Experience developing dashboards, decision‑support tools, or operational automation platforms.
  • Experience supporting model transparency, benchmarking, and audit‑ready documentation.
  • Experience conducting user training and supporting adoption of new technologies.
  • Bachelor's degree in computer science, data science, engineering, or a related field.
  • Relevant certifications in AI, machine learning, cloud, cybersecurity, or DevSecOps disciplines.

Benefits

Venatore offers a competitive benefits package designed to support the well‑being of our employees, including:

  • Paid Time Off (PTO)
  • 10 Federal Holidays
  • 401(k) with company matching
  • Medical, dental, and vision insurance
  • Paid parental leave
  • Paid military leave

Requirements

  • Demonstrated experience designing, building, testing, and deploying artificial intelligence or machine learning solutions in operational environments.
  • Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, or similar tools.
  • Strong programming skills in Python and experience in Linux-based environments.
  • Experience with data preparation, labeling, feature engineering, ETL processes, and model validation.
  • Familiarity with secure software engineering practices, APIs, containerization, and modern deployment approaches.
  • Working knowledge of cybersecurity practices, including protection of Controlled Unclassified Information and Federal Contract Information.
  • Experience producing technical documentation, training materials, and briefings for varied audiences.
  • Ability to work full-time on-site at Westover Air Reserve Base in Chicopee, Massachusetts.
  • Ability to operate effectively in a structured government environment.
  • Strong communication, collaboration, and problem-solving skills.

Responsibilities

  • Design, train, validate, optimize, and deploy artificial intelligence and machine learning models addressing Base Civil Engineering mission needs.
  • Develop and enhance solutions for contract and revision analysis, energy monitoring and optimization, and snowfall recovery and readiness.
  • Transition pilot and beta capabilities into reliable operational tools for government users.
  • Apply predictive modeling, statistical analysis, and automation to extract actionable insights from structured and unstructured data.
  • Define model performance metrics, operational benchmarks, and improvement plans aligned with mission requirements.
  • Collect, prepare, cleanse, label, and validate data from multiple government-owned sources.
  • Build scalable data pipelines, feature engineering workflows, and repeatable model training processes.
  • Analyze historical and real-time data to identify trends, inefficiencies, and operational risks.
  • Perform model retraining, tuning, benchmarking, and performance monitoring.
  • Maintain traceability between data sources, model outputs, and operational use cases.
  • Integrate AI solutions into secure, local, and air-gapped environments in accordance with government requirements.
  • Support development, test, and production environments within approved security boundaries.
  • Implement secure coding practices and cybersecurity controls to protect Controlled Unclassified Information and Federal Contract Information.
  • Ensure alignment with security standards, AI ethical principles, and compliance requirements.
  • Coordinate system updates, upgrades, and changes with government stakeholders and IT personnel.
  • Develop and maintain system documentation, user guides, technical manuals, and operational materials.
  • Conduct recurring monthly training for Air Force personnel on AI tools and workflows.
  • Prepare and deliver monthly status reports covering progress, risks, and performance.
  • Support patching, bug fixes, model updates, and sustainment activities.
  • Deliver briefings, demonstrations, and written updates to leadership and stakeholders.
  • Collaborate with government leads, users, and support teams to align solutions with mission objectives.
  • Participate in meetings, working groups, and technical discussions as required.
  • Coordinate testing, validation, and release activities.
  • Identify process gaps, data limitations, and integration risks, and recommend improvements.
  • Maintain professional accountability in an on-site, mission-focused environment.

Benefits

Paid Time Off (PTO)Federal Holidays401(k) with company matchingMedical insuranceDental insuranceVision insurancePaid parental leavePaid military leave

Skills

AWS GovCloudAzure IL5/IL6CeleryContainerizationD3.jsDatabricksDjangoDockerETLKerasKubernetesLinuxMachine LearningPostgreSQLPyTorchPythonSparkSQLTensorFlowVersion Control

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