Batch ingestion, batch transformation, storage, presentation via BI tools (AWS Quicksights)

Built with AWS s3, AWS lambda functions, AWS SQS, AWS kinesis firehose, redshift, dbt.

Implemented generalized producer consumer framework that eliminated bottlenecks for scaling the previous pipeline design by streaming data instead of batch processing.

Reduced latency from event capture to end reporting from 1 hour to < 1 minute.

Ingested ~1MB/min during peak loads.

Built with the custom python pipeline framework, AWS SQS, kibana, redshift, dbt, and elasticsearch.

Represented the UC Davis student body and persuaded prospective students to attend UC Davis.

Did it all while walking backwards!

Prototyped Machine Learning models using SciKit Learn in iPython Jupyter Notebooks.

Optimized model parameters and design

Worked with PySpark and Panda Dataframes

Performed batch data processing on large volumes of server log data.

Built data ingestion pipelines for feature engineering

Designed and optimized feature vectors

Worked with Docker, Knex SQL, DynamoDb, Redis, CircleCI, AWS S3, and AWS CloudFront.

Built web applications using HTML/NodeJs/CSS, React, JQuery, Bootstrap, and React Semantic-UI.

Created algorithms for NLP entity extraction using Google Cloud Platform’s Natural Language API

Built serverless backend applications on AWS Lambda using the "Serverless" framework.

Integrated numerous third party API’s via Webhooks.

Developed MATLAB scripts to analyze large amounts of financial data to supplement the audit of each business unit.

Managed and lead a team of 12 other students in the following tasks:

Held weekly commission meetings to evaluate the impact of spending legislation.

Generated official financial and business recommendations to the ASUCD (student government) Senate on the appropriation of a $14 million dollar budget.

Performed regular financial audits of 26 on campus Strategic Business Units.