Senior Data Scientist: AI, MLOps & Resource Optimization

Unissant; Washington (District of Columbia); On-site; USD 140,000 - 190,000; Full time

Job summary

Unissant, Inc. is seeking a Senior Data Scientist to join our Washington, DC team in support of DHS/ICE LESA. You will lead advanced ML/AI projects, oversee MLOps, and drive data-driven decision support across enforcement and logistics domains.

The role emphasizes architecture, model governance, and collaboration with data and enterprise architects to scale AI workloads. On-site in Washington, DC, with senior leadership exposure and DHS accreditation readiness.

Qualifications

• 10+ years of experience in data science, ML, or applied AI research with federal missions preferred.
• Experience with advanced ML/AI: deep learning, ensemble methods, Bayesian methods, and multi-objective optimization.
• MLOps experience: versioning, monitoring, CI/CD for ML, deployment in HPC/cloud environments.
• Experience with DES modeling, operations research, and logistics optimization.

Responsibilities

• Architect, develop, and operationalize advanced ML solutions including CNNs, RNNs, Transformers.
• Plan and design deep learning algorithms for multi-objective optimization in resource allocation.
• Lead MLOps activities: versioning, monitoring, CI/CD, retraining workflows.
• Prepare models for DHS accreditation with proper documentation.
• Develop and govern DES models to support forecasting and decision-making.

Skills

Deep learning

ML/DL leadership

MLOps

Forecasting/Optimization

Data visualization

Education

Bachelor's degree in Computer Science or related

Master's degree or PhD preferred

Tools

TensorFlow

PyTorch

Keras

MLflow

DVC

ArcGIS

Tableau

Job description

Unissant, Inc. is seeking a Senior Data Scientist to join our Washington, DC team in support of DHS/ICE LESA. You will lead advanced ML/AI projects, oversee MLOps, and drive data-driven decision support across enforcement and logistics domains.

The role emphasizes architecture, model governance, and collaboration with data and enterprise architects to scale AI workloads. On-site in Washington, DC, with senior leadership exposure and DHS accreditation readiness.