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- Design, develop, and evaluate machine learning models for applied research and experimentation
- Collaborate with multi-disciplinary teams to prototype and deploy data-driven solutions in dynamic environments
- Conduct exploratory research and pilot projects, focusing on Privacy-Enhancing Technologies (PETs) adoption
- Analyze and interpret experimental results to diagnose model issues and improve performance
- Communicate findings and insights effectively to technical and non-technical stakeholders
- Strong foundation in Data Science and Machine Learning, including model development and experimentation
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and scikit-learn
- Experience in experimental design, evaluation, and applied research methodologies
- Ability to synthesize academic research and apply it to real-world data challenges
- Comfortable working in ambiguous environments, exploring novel problem-solving approaches, and engaging with agency users
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