Senior Data Scientist

What you will do:

• Investigate and analyze exquisite multimodal datasets to identify and expose hidden patterns and trends
• Develop, evaluate, and apply novel AI/ML models to automatically derive valuable insights for defense and intelligence analysts
• Think critically about robust modeling capabilities that generalize to support broad application against high-impact national security problems
• Collaborate with diverse teams to explore new domains and data modalities, investigate state-of-the-art research, tackle emerging problem spaces, and mentor others
• Who you are:
• Active Secret security clearance, for which U.S citizenship is needed by the U.S government
• MS degree with 3+ years of experience, and/or PhD in Statistics, Data Science, Applied Mathematics, Computer Science, Physics or other related discipline (or equivalent experience)
• Desire to tackle challenges, develop new skills, and explore unsolved problem spaces
• Experience developing and applying AI/ML methods to real-world data science problems, especially in settings where data is sparse, noisy, and/or high dimensional
• Familiarity with various algorithmic techniques such as Bayesian methods, predictive models, reinforcement learning, deep learning architectures, and large language models
• Comfortable creating data visualizations and communicating technical findings
• Proficient with Python and the traditional data science and machine learning stack, including NumPy, Pandas, scikit-learn, PyTorch, and matplotlib
• Demonstrated ability to collaborate effectively within cross-functional teams and communicate with customers and end users
• Even better:
• Familiarity with geospatial and/or spatiotemporal data
• Demonstrated ability to conduct and lead research tasks amidst uncertain conditions with minimal oversight
• Experience working with large datasets (> 100 GB) and familiarity with big data infrastructure and frameworks such as AWS, Hadoop, Spark, Dask, or MapReduce
• Solid understanding of software engineering principles, including testing, scalability, observability, maintainability, and performance optimization