Applied Research in Government Operations builds, operates and maintains pioneering public data infrastructure to transform how basic public services like water efficiency are delivered. We've helped partner California water utilities save over \$20 million, informed the optimization of half a billion more and laid the foundation to ensure water reliability no matter what the future holds.
Core Challenge
Our projects have been very successful though could use more engineering resources to help the rocket soar higher, faster.
Projects
Water Data Analytic Software:
We deploy open source analytics to help water utilities navigate historic shifts and the generational challenge of climate change. Our tools support agencies in meeting critical goals like water efficiency and revenue stability. You can see our legacy analytics portal here: https://demo.californiadatacollaborative.com/smc We are currently developing a next-generation analytics platform built on top of Python Flask to replace our legacy stack of Rshiny and RMarkdown applications. We are a very lean team and would appreciate more engineering support as well as general mentorship from more experienced engineers or product managers. Data analytics software supporting operational decisions is one of the core pillars of our organization (the other pillars are applied research and streamlining mandatory reporting). In addition to being central to what we do, our decision support software tends to be the “wow” factor that first engages potential agency partners and gets them curious to participate and support some of our other important but less flashy work.
Commercial Business Classification:
We have an ongoing applied research project to develop a pipeline for classifying customers into specific business classifications given only an address. Our aim is to make use of multiple data sources (e.g. Yelp, Google Places, other business databases) to predict a classification for a customer. This is a very difficult project and progress so far as been stop and go. Our ideal end result would resemble a python library that takes f(address) -> classification but this is complicated by factors like strip malls (many businesses served by a single water meter) and generally poor data quality. Our hope is that by fusing multiple data sources we can arrive at something useful for our water agency partners. This project is more experimental and open-ended, and making progress here would be a substantial advance for some specific problems in the water sector.
Core Skills Needed
Project 1: Web Development, Web mapping, Javascript/Vue, Web Design, Python Flask
Project 2: Python, Data Engineering, Entity Resolution, Data fusion
General mentorship skills: UI/UX Design, Product Management
Applied Research in Government Operations builds, operates and maintains pioneering public data infrastructure to transform how basic public services like water efficiency are delivered. We've helped partner California water utilities save over \$20 million, informed the optimization of half a billion more and laid the foundation to ensure water reliability no matter what the future holds.
Core Challenge
Our projects have been very successful though could use more engineering resources to help the rocket soar higher, faster.
Projects
Water Data Analytic Software:
We deploy open source analytics to help water utilities navigate historic shifts and the generational challenge of climate change. Our tools support agencies in meeting critical goals like water efficiency and revenue stability. You can see our legacy analytics portal here: https://demo.californiadatacollaborative.com/smc We are currently developing a next-generation analytics platform built on top of Python Flask to replace our legacy stack of Rshiny and RMarkdown applications. We are a very lean team and would appreciate more engineering support as well as general mentorship from more experienced engineers or product managers. Data analytics software supporting operational decisions is one of the core pillars of our organization (the other pillars are applied research and streamlining mandatory reporting). In addition to being central to what we do, our decision support software tends to be the “wow” factor that first engages potential agency partners and gets them curious to participate and support some of our other important but less flashy work.
Commercial Business Classification:
We have an ongoing applied research project to develop a pipeline for classifying customers into specific business classifications given only an address. Our aim is to make use of multiple data sources (e.g. Yelp, Google Places, other business databases) to predict a classification for a customer. This is a very difficult project and progress so far as been stop and go. Our ideal end result would resemble a python library that takes f(address) -> classification but this is complicated by factors like strip malls (many businesses served by a single water meter) and generally poor data quality. Our hope is that by fusing multiple data sources we can arrive at something useful for our water agency partners. This project is more experimental and open-ended, and making progress here would be a substantial advance for some specific problems in the water sector.
Core Skills Needed
Current Tech Stack
Project contact Christopher Tull, Project Manager