Owned web service which processed 100 logs/second coming off device 24x7

Owned Jenkins batch job service processing 1000 batch jobs per day

Led our transition from on-prem to cloud based Kubernetes deployments

Built CICD pipelines to support cloud migration, automated unit testing and linting

Created an integration test suite for the web service. Created a culture of test driven development (TDD) and code reviews. Created a playbook for the team and our sibling SRE team to handle production incidents

Refactored web service code base to support batched API calls thus reducing cross data center networking and speeding up log processing by 20%

Built and migrated new backend API across 3 webservices to speed up log processing by 10% and transitioned 93% of calls to old endpoint to new endpoint.

Split apart our monolith into 5 separate services and migrated 2 of them from Python2 to Python3

Tech stack - Python, Flask APIs, SQL, Kubernetes, Docker, Docker, Grafana, Hubble, Splunk, Jenkins, Object Store

Build and maintain tooling and backend services in Python that support Quantitative traders (Quants).

Primarily writing code in Python and SQL.

Tech stack: Python, Flask APIs, SQL, managed Kubernetes, Git, Docker, Grafana, Parquet, Arrow, Object Store

Led the successful launch of Jupiter’s operational wildfire risk product (FireScore Ops)

Led Product Management, Science, Technical Project Management (Jira and Confluence), and Business Development on a team of up to 15 in a matrix-based organization at an early stage startup

ETL pipelines running every 5 minutes 24x365 in Python, Bash, and Postgres with data churn of ~200Gb/day

Achieved 14 weeks of zero maintenance operations through fault tolerant reliability engineering

Created web based dashboard visualization using Javascript, HTML, CSS

Invention and commercialization of Intellectual Property through licensing agreement with Univ of Nevada

Training and operationalization of logistic regression model in Python using Scikit-learn to forecast wildfire risks

Architected, constructed, and operationalized state of the art realtime NWP model for forecasting wildfire danger and utility power shut-off events

Developed and taught Python Programming for Atmospheric and Hydrologic Science applications, UNR Graduate School (2018, 2016, 2014). Mentored many graduate students

Funding: $2.1M as Primary Investigator (2013-2020) from sponsors: NSF, DOD, DOE, Google, Moore Foundation

Service: Amer. Met. Soc. Wildfire, Technology and Risk Committee (2019-2022), and Renewable Energy Committee (2015-2018), UNR Atmospheric Science Graduate Admission Committee (2013-2018)

Popular media: LA Times, Bloomberg News, Daily Beast, NPR Across the Nation, KTVN, Discovery Channel

Publications and Citations link: https://scholar.google.com/citations?user=INKTFyYAAAAJ