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Software Engineer

JPMorgan Chase

Leverage my technical expertise to develop and optimize communication platforms for Consumer and Community Banking customers

• Led a database migration for 10M records and hundreds of SPROCs to Java, boosting accuracy from 50% to over 99%
• Collaborated with QA engineers to effectively triage issues in lower environments, resolving most within the same day
• Mentored team members on new codebases and processes, allowing the team to have a greater impact across Chase Communications
• Supervised production releases outside of business hours to minimize customer impact, carefully checking for errors, exceptions and anomalies to ensure smooth deployments
• Acted as the primary point of contact for all data streaming platform customers, coordinating efforts across 12 teams and 50 people. Ensured technical requirements were captured and communicated the specifications for new features to the development team. Debugged customer pipelines using Gaia Kafka, Amazon S3, Amazon Athena and Kubernetes to facilitate their timely delivery to production

Software Engineering Intern

Apple

Improved a regression testing system for machine learning tagger models used by the News App, decreasing the runtime for regression testing by a factor of 12x and eliminating pain points for model scientists

• Consolidated 5 PySpark jobs into 2 jobs and eliminated a daily Java cron improving run-time and reducing brittle inter-job dependencies by eliminating approx. 750,000 intermediate directories and files
• Identified a bug in the taggers due to a lack of robustness to different encodings while validating the new system
• Used Pyspark, Hadoop, Kube, Yaml, Rio and Artifactory; focused on efficient, reusable, and testable code

Data Science Intern

Amazon

Developed a summarization backend which creates TLDRs for tax documents, saving Amazon approx. $1M per annum

• Used AWS Lambda, API Gateway, RDS, and S3 for an efficient, cheap, and easy-to-maintain backend
• Collaborated with Amazon Tax specialists to understand how Amazon Tax previously generated TLDRs as well as to evaluate how useful state-of-the-art summarization techniques as compared to heuristic approaches would be to Amazon
• Identified and addressed a critical encoding bug in tagger models
• Created a website using React and following RESTful principles which allows non-developers to adapt the summarization algorithm, allowing Amazon Tax to easily improve and extend the summarization backend resources

Machine Learning Consultant

Test Innovators

Built on deep learning literature on autoencoder architectures in NLP to automate essay grading

• Analyzed various interventions to assess their impact on students, informing business strategies and sales efforts
• Used NLTK, Tensorflow, Seaborn, Scikit-Learn, Pandas and Numpy on Google Colab

Research Assistant

Davidson College Computer Science Department

Implemented an efficient, distributed agent that uses Monte Carlo Tree Search (MCTS) to find optimal moves in Hex

• Distributed MCTS using per-thread work queues on compute nodes scheduled by one controller node

Research Fellow

Davidson Research Institute

Developed a multi-threaded library that facilitates high-performance computation across nodes using Message Passing Interface, atomic operations, allowing researchers to pass anonymous functions using RDMA between compute nodes

Software Engineering Intern

Test Innovators

Wrote a validator service in Python that runs on an AWS server, validating millions of test sections completed on the online test prep platform, to ensure that data-driven student recommendations are based only on valid data

• Collaborated with product, development, and leadership teams to understand the needs of Test Innovators
• Optimized the service by interpreting data efficiently and minimizing communication between the validator and the SQL server, resulting in an algorithm that had previously taken weeks to run executing in less than an hour
• Ensured code was readable for future developers and onboarded an engineer to the project upon internship completion

Masters

University of Massachusetts Amherst

Computer Science

• Machine Learning
• Algorithmic Fairness and Strategic Behavior
• Algorithms for Data Science
• Advanced Algorithms
• Information Retrieval
• Secure Distributed Systems
• Neural Networks
• Applied Numerical Optimization
• Digital Forensic Systems

Bachelor of Science, Cum Laude

Davidson College

Computer Science, Political Science

• Data Structures
• Discrete Structures
• Programming Languages
• Networks and Systems
• Computer Organization
• Machine Reasoning
• Distributed Data Structures
• Database Systems
• Analysis of Algorithms
• Machine Learning
• Linear and Discrete Optimization
• Distributed Artificial Intelligence
• Algorithmic Game Theory

Distributed Artificial Intelligence

Davidson College Computer Science Department

Defended my undergraduate honors thesis on distributed artificial intelligence

High-Performance Distributed Computation

Davidson Research Institute

Presented a library of functions that performs high-performance computation across many compute nodes at a poster session

On Error Free Transformations and Applications to Polynomial Equations

MathFest

Presented modifications of root finding methods in which we extend the working precision of both methods through floating-point techniques