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A Day in the Life of a Data Analytics Intern

January 11, 2019 by Richard Todd

Guest post by Namrata Kolla – a proud IP alumnum.

Group of interns with mayor Jenny Durkan

Nam finds herself well-positioned under wall-mounted arrow

 

On the first day of my internship, my manager took me to Caffe Vita[1], a coffee shop a few blocks from City Hall. When I asked him which projects I would have the chance to work on, he slapped a white sheet of paper on our tiny tabletop and said, “Here’s a Kanban!”.

My first thought was, “What’s a Kanban?”

My second thought, “Holy smokes, that’s a lot of options!”

Until I started my internship, I did not realize the breadth of services that municipal governments provide. I had some vague ideas via my interactions with the City, but through my Data Analytics internship I suddenly saw many more. Below are three takeaways from my time as an official Seattle government insider:

1) City government collects a lot of awesome, important data.

Just last month, I was listening to a presentation where my professor stated that the three organizations that have the most data in the world are Google, Facebook, and Amazon. I spoke up in class that day to tell the professor he forgot a big one: government!

Our city has some of the richest datasets in the world. While there are valid reasons to be wary about data collection and storage, government data, in particular, are pretty special. My favorite reason is that government data tend to be more inclusive than what most private companies can generate. For example, one of Amazon’s biggest datasets is the purchasing behavior of millions of people. At the same time, in the service of making its services better, Seattle City Light collects data about the quality of its power supply to almost every household in Seattle – not just those people that have computers or use particular websites. To protect this data, the City has some of the strongest privacy and data security policies in the world.

The power and extent of administrative data was a big lesson during my internship. There are many obstacles in the way of using administrative data to their full potential, some of which were placed with purpose. But, I feel that too few administrators are aware of how much more certainty and nuance they could have in their program decisions if they better (and safely) employed the data we already have at hand.

2) Analytical innovation will never be as important as trust and communication. 

After spending 70% of my time crunching numbers on a computer screen, 20% percent talking to partners in meetings (and 10% getting coffee), I found time and time again that the conversations I had in the 20% of my time decided the fate of my projects far more than any discovery I made in that 70%.

While getting desk time with no distractions is definitely something to relish, analytical problems are always easier to solve than organizational problems. When I ran into a bug trying to manipulate shapefiles from the American Community Survey, I spent an hour brainstorming with a colleague in public utilities, two hours on the phone with the University of Washington’s statistics department, and at least four hours with Dr. Google. When I ran into hurdles trying to access data to complete a project for a department partner, I spent an hour sending emails and three hours in discussions. While the first problem may have been more laborious, I never felt as stressed as I when I was trying to solve the second problem. I usually feel confident that I can solve a technical problem or find someone to help me, but I am rarely confident about problems requiring motivating people. Fortunately, I have been able to observe my colleagues in the Innovation & Performance (IP) Team and the City Budget Office and learn more about how to communicate intent and value building relationships over short-term success.

 3) Analyzing data in government doesn’t have to be a lonely job.

I heard myself and several City data analysts mention feeling lonely at some point or another while trying to solve day-to-day problems. While this is not unique to our role, often there are only a handful of people who use data in the particular way that we do and there is nobody else to ask for help. The silos that naturally grow from the organizational structure of the City also made it hard for me to find help in other departments when I initially started my internship.

However, I was lucky that the IP team organizes monthly City Performance and Data Science meetings where I had a chance to meet city workers in similar problem spaces. Additionally, the nature of our work being conducted in departmental partnerships helped me build authentic connections with other analysts while working in the weeds. Nothing cultivates a relationship with another person better than going through something hard, and I have found that to be as true in city government as in my personal life!

Looking back at my time on the IP team, I am so grateful to have been a part of this family. It has made a huge difference in my life to see city workers so passionate and committed to bettering communities and making long-term, systemic change. While there were countless challenges, there were many more celebrations and I have only become more humbled and excited to pursue a career in public service.

 

[1] Other excellent coffeeshops are available and are indeed patronized by the IP team

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