Lessons learned from my adventures in data, cities, and the civic tech community
My 10 week journey as a Coding it Forward Fellow in New York City’s Department of City Planning
At the end of my time at UC Berkeley, I knew a few things about myself. One: I wanted to be a data scientist, or in some form, think deeply about data to derive insights. Two: I wanted my work to directly apply to some area of our shared daily lives, rather than only theoretical or serving a select few people. Three: What piqued my interest for the last few years of college were cities and urban planning.
I loved (and still do) thinking about cities as complex systems where many different areas of our lives come together. How we plan, maintain, and sustain our lived spaces and urban environment enormously impacts our lives. I wanted to explore this web of connections using the data tools I’d spent time in college honing in.
So, I was elated when the NYC Department of City Planning offered me a Fellowship spot in their data engineering team. I’d followed their open-source work from afar, inspired by the dedication to transparency and openness that the City showed. In June, I could also begin my adventure into this world of data and cities!
For the ten weeks of the Fellowship, my co-Fellow Ali and I were tasked with exploring making a potential new data product, one that would allow NYC planners to analyze and understand historical spending patterns for where the City has invested, and do so both temporally and spatially. Which neighborhoods have been under or over-invested in? In what types of projects or agencies? How have these patterns changed over time? The work was enthralling to me: being able to answer these questions systematically and using data analytics tools would be an important guide to how the City invests in the future.
Our road to having a new product was filled with exciting discoveries and challenges as we navigated exploring, scoping, and ultimately building and iterating our pipeline. In the ten weeks of the Fellowship, I made my first Pull Request on GitHub, got to present to the Executive Capital Planning team with Ali two times, learned more about each step of the (usually hidden away) data-creation pipeline, and got more familiar with the data products that the Data Engineering team and everyone else at DCP maintains. But, here are some of the lessons I will cherish the most.
#1: Empathy and listening are the most useful qualities for a public interest technologist
As I realized soon after we started working, an agency doesn’t always need to hurry to adapt to the hottest tool in the market. What is much more useful is thinking critically about what each technology we deploy is doing and how it affects people. For instance, DCP has realized that many New Yorkers would benefit from seeing how much money the city is spending or the current demographic breakdown of their neighborhood.
These tools have been carefully thought out in each step of designing them, and they result from listening to people’s needs. Other agencies needed their Fellows to compile a database that keeps track of the agency’s data sources or improve existing marriage forms to ensure same-sex couples are served equitably. These needs arise from concrete problems; it takes people who can listen well to implement these solutions empathetically.
#2: Keeping track of what happens each week is very helpful
This next lesson is a tip I learned early in the Fellowship. As we heard from our orientation panel at New America in Week 1, keeping some a journal is a very good idea. It can be easy to get sucked into the pace of work, so setting some time each week to jot down what you are learning, accomplishing, or what you find the most interesting (or not) can be very helpful when you are planning out your career.
It is likely that you, like me, are relatively new to the civic tech space or are still navigating what you would like to pursue: think of the Fellowship as a very valuable experience to find some of these passions. As a bonus, you can look back to the incremental accomplishments you are making with your agency. Seeing how the technical work we were doing translated into helping others do their work better was very rewarding!
#3: The importance of people
In her book “Recoding America,” Jennifer Pahlka talks about the importance of the people she calls “insiders,” those workers who maintain and transform digital systems within their organization, making them better. For instance, she talks about the role of Yadira Sanchez in spurring a transformation in how the digital teams operated and brought policy ideas into an efficient implementation. She also talks about the creation of the US Digital Services and 18F, the need for in-house tech talent, and the current initiatives in bringing more early-career workers into these roles.
Pahlka makes the case that many current issues with implementing complex policies into practice or offering digital services could be addressed by hiring early-career people into positions like engineering, design, or research and increasing the government’s emphasis on policy implementation.
Coding it Forward is a unique program serving these needs. The new connections with young people interested in working in government are the most exciting takeaway from the Fellowship! Meeting so many thoughtful and talented people fills me with optimism for the future, and I can’t wait to see what everyone will be up to.
This last lesson brings me to my biggest takeaway: through the ten weeks of the Fellowship, I learned a lot about how everything fits together in terms of code, but the people impressed me the most. Everyone at DCP was incredibly friendly and open: they remembered the random facts I shared over our biweekly meetings or helped answer my obscure questions about various parts of our codebase.
The members of the Data Engineering team were generous with their knowledge and time, making my experience immeasurably more valuable. I’ll walk away from my time as a Fellow, having learned how a modern data engineering team operates and inspired by people’s passion and dedication to improving their communities’ lives.
Dea Barshodi
is a data scientist and software engineer with an M.S. in Computer Science from George Mason University. This summer, she worked at the U.S. Census Bureau on the Business Frame Team, building an end-to-end data pipeline from scratch in Python to convert millions of pages of minimally structured PDF files into formatted database entries, to better inform policymaking and research, enhance data discoverability, and reduce false matches.
