At Palantir (NYSE: PLTR), we're helping the world's most important institutions use their data to solve their most urgent problems. Our software lets our customers integrate and analyze all of their data so they can answer questions that they couldn't before. From delivering disaster relief to building safer automobiles, we're honored to help make our partners better at their most important work. 

Together with our customers, we're building the future of national security, healthcare, energy, finance, manufacturing, and more. And we need bright minds from around the world to help us.

Took an extra year for enrichment to work through the majority of a mathematics major including coursework on probability with proofs, number theory, abstract algebra, real analysis

University of Maryland

University of Maryland College Park

Montgomery College

Software Engineer

• Developed React/Redux/Node SPA with code reuse from existing online learning platform.
• Produced reusable React component library which decouples layout, component, and content populated from parsed YAML to act as a cms allowing other teams to update content.
• Leveraged CSS modules to create reusable UI styled components for increased modularity.
• Designed a DSL to express Redux logic and generate reducers to reduce engineering time.
• Implemented an interpreter to parse a domain specific language and perform immutable updates on Redux state.
• Implemented a Depth First Search algorithm to infer update locations in arbitrary Redux state-trees.
• Wrote Integration and Unit tests to enable rapid language redesign while maintaining code and API correctness.

• Designed a denormalized HStore schema in PostgreSQL to reduce a 50k row indexed write query latency by 90%.
• Utilized Haproxy, NGINX, and Vagrant to implement session-based load balancing for a virtual machine application layer on multiple cloud hosts and development environments, ensuring high availability.
• Implemented a hotfix for OpenLayers.js caused by a Google Maps update preventing weeks of frontend down-time.
• Employed a MCP numerical optimization algorithm for an electricity market model distributed across commodity hardware to reduce around-the-clock runtime from several weeks to a few hours per run, ~99%.
• Architected a design that decouples MCP model and scaling code to save ~20% of team engineering time.

Research Team

• Taught the first pilot Data Fundamentals course for Booz Allen Hamilton and served as a key member in its design. The pilot was accepted and will train 5,000 data professionals.
• Managed 300 hours of workshop-style classroom time including lecturing, live coding, and in-class troubleshooting of student code and git workflows.
• Achieved a top-ranking Net Promoter Score of 71 in my latest part-time class.
• Provided technical mentorship on ~100 10-week data science projects through code review and project scoping.

Lead Data Science Instructor

• Developed Python Machine Learning code and Jupyter Notebooks in close collaboration with a Data Science team to ensure technical clarity and correctness of concepts across ~100 GitHub Enterprise repositories for a global audience.
• Improved the Data Science Immersive curriculum covering Python, data manipulation, databases, supervised learning, clustering, dimensionality reduction, and introductions to deep learning.

Subject Matter Expert: Data Scientist

Associate Instructor for General Assembly's 11-week Data Science course.

Associate Instructor (Data Science)

Teaching Assistant for Machine Learning with Text in Python for several class sessions. Responsibilities include clarifying advanced programming and machine learning topics on student's in-class and real world projects and providing code review for student homework.

Machine Learning/Text Classification, Python

• Data wrangling and exploration on a home energy efficiency survey based in Italy.