Trained a deep neural network for lidar semantic segmentation using Tensorflow.

Built data pipelines for extraction, storage, and indexing labeled data and Python APIs for querying and curation of datasets using Python, Kubernetes, SQL, and ROS.

Led the quarterly planning and roadmapping process for Product at Springboard.

Established and evangelized processes for quarterly planning, continuous intake, and prioritization.

Drove alignment on cross-function priorities with the general managers, operations and engineering team leads.

Developed and executed the Springboard Data Platform strategy. Instrumented over 325 user events using Segment, RabbitMQ, Celery, Google Big Query and ChartIO.

Prototyped a job matching model using Keras and TensorFlow to reduce job match-time from 4 days to 24 hours.

I worked on a random forest model to identify the top 3 predictors of student churn, improving retention by 15%.

Developed and executed the Springboard Outcomes strategy. Built a Job Search Workflow product to increase weekly job search compliance from 25% to 80% in 6-months.

Built and launched an event-based intervention platform to deliver notifications to increase user activation from 35% to 75%.

Modernized deployment systems using Docker, Kubernetes, and Google Cloud Platform, saving $50K annually.

Led the migration from AWS to GCP; removed 3 single-points of failure, set up the continuous deployment pipeline, achieved 25% faster build times, improved scalability, and better controls for rollbacks.

Built a GraphQL API layer which resulted in 2x faster performance, and speeding up development time.

Curriculum Management System

Calendaring & call scheduling

Student <> Mentor matching algorithm