Machine Learning Engineer / Data Scientist

What you’ll own.

• Prepare and analyze data, engineer features, select algorithms, train models, tune hyperparameters, and evaluate model performance.
• Develop models for forecasting, anomaly detection, risk prediction, optimization, classification, natural-language processing, or pattern recognition.
• Implement data preprocessing, model testing, validation, bias evaluation, explainability, documentation, and production deployment.
• Build model APIs, batch inference processes, scoring pipelines, feature pipelines, and integration points with agency applications.
• Develop model documentation, evaluation reports, experiment records, model cards, and operational guidance.
• Support monitoring for performance degradation, bias, drift, reliability, security, and ongoing model improvement.

Experience that prepares you for the work.

4+ years in data science, machine learning engineering, statistics, analytics, or software engineering. Strong Python and experience with scikit-learn, TensorFlow, PyTorch, SQL, data preparation, model evaluation, and cloud ML platforms preferred.