I'm one of the new Bay Area chapter leads for Illuminate AI! I help make events better and build this community to the next level!

I'm advising Mage on how to make a data engineering friendly Airflow competitor that will be the next generation of job orchestration!

I’ve invested in SylphAI because I’m passionate about building community in AI that helps everyone meet their growth goals and fulfill their potential

Changed Airbnb's availability definition from "did a host set a rule that blocked this night" to "can a trip be booked that contains this night" Consolidate the availability definition across the company. Saving >500 TBs in the cloud and shrinking the data set to 3% its old size.Decreased the landing time of Airbnb's unit economics dataset from 3 days to 1 1/2 days. Built a long-term roadmap to further increase the quality of this critical dataset. Improved the quality of online systems at Airbnb to be easily compilable by Spark pipelines to compute metrics offline. Lead a team of 6 engineers to deliver on the MIDAS initiative to increase the data quality of the Commercial Products org. Upleveled smart pricing at Airbnb by improving the feature engineering and latency of the data used to train the smart pricing model.

I took a year off. I spent 2 months in Puerto Rico the first two months of the pandemic swimming a mile most days in the ocean. I spent 3 months road-tripping and seeing all the national parks in the western US. I got over 100 wins in Call of Duty Warzone (top 1% of players)I adopted a Siberian Husky

Built a machine learning feedback system that allowed security engineers to label corporate user behavior as risky or not risky.Built Asset Inventory - a graph database solution that is a map of all of Netflix's cloud infrastructure.

I built a pipeline that measures the cloud infrastructure impact on AB tests, saving Netflix millions by allowing them to make smarter AB test rollout decisions.

- Managed a 10 PB+ Hive data warehouse- Consolidated and conformed company-wide growth metrics (across WhatsApp, Instagram, Messenger, and Facebook) into a single, company-wide view. - Optimized machine learning feature set generation pipelines (200+ TB/day) from having a 4 day latency to having a 1 day latency. While also dropping compute costs for those pipelines 4x. - Reduced core notification data set latencies from 36 hours to < 8 hours. - Migrated 50% of notifications pipelines from using Hive to use Spark, Presto, or real-time streaming.- Cut compute cost from notifications pipelines by 40% over the course of 9 months.

I run the technology show for a startup company I helped found called Red Pika Labs. The company tech stack is completely in JavaScript right now. Our first product, Art Lineup (https://www.artlineup.me) launched in March 2017 and has been getting better ever since then!Tech stack is:AngularJS frontend on webReact Native frontend on mobileNodeJS backendPostgres Database

-Microservices in Node.js and Docker-RabbitMQ message broker-Entity extraction and natural language processing with Apache Spark and 3rd party services-Big data with Accumulo and Hadoop-Modern front-end systems with Angular.js and data visualizations in D3.js

-Implement ETL processes in Hadoop-build custom MapReduce jobs, Hive UDFs, and Pig UDFs-design data warehousing approaches with Teradata-data visualization with Tableau and D3.js-create data streams using Apache Spark and Apache Storm

- Create data visualizations using Tableau - Database management and migrations- Data mining in Python- Data analysis and management using SQL - Setting up and managing graphical databases such as OrientDB and AllegroGraph- Automate ETL processes using Pentaho and SQL

Data visualization using Tableau and data analysis using SQL and R.

Tutor math subjects varying from pre-algebra through ordinary differential equations.

I stocked the grocery departments shelves.