This is the first post in what will be an ongoing series to feature an average workday of employees in various roles on the MTA Data & Analytics team. We hope these posts give a peek into what it’s like to work with data at the largest transit agency in the United States!
6:30 a.m.
Good morning, New York! I start off most mornings with a run along the West Side Highway. Being near the water is my favorite way to start the day.
8:15 a.m.
After a quick shower and breakfast, I hop on a 2/3 train and head downtown to the MTA office in FiDi. On my way in, I notice that one of our countdown clocks isn’t displaying any information, so I report it to our internal #getitfixed Slack channel. This channel provides a quick and easy way for internal employees to flag things across the system that need some extra care and attention.
9:00 a.m.
I have no meetings until noon today, so I’m taking advantage of the quiet time to tackle a couple of deeper work tasks.
First, I’m code reviewing two pull requests for metrics.mta.info, the MTA’s performance dashboard that serves as the front door to our Open Data program. One pull request fixes a small bug on an Elevator and Escalator Availability page, while another repoints the data source for a page to data.ny.gov. Our goal is to have every visual on the site pointing to Open Data, and we are a handful of datasets away from achieving that, so I’m really happy that both pull requests can be approved without any further changes.
Next, I continue work on a charter for a project whose goal is to make all data published in the Bridges and Tunnels Committee Book available through Open Data. There are lot of stakeholders and data sources needed for a project of this size, so we are trying our best to define and agree upon what is in scope (and what is not!) before just blindly getting started.
Read more about the MTA’s Open Data program and upcoming datasets on deck for release.
10:45 a.m.
I can sense my emails and Slack messages piling up, so I take a break from working on the project charter to respond to some of the more critical messages. One of the messages is from a team member who has realized that she is missing access to underlying data necessary to build one of our datasets for an upcoming release. We decide to have a quick meeting to discuss so that we can try and move quickly on next steps to gain access to the missing data.
12:00 p.m.
I join a quick touch base with the other managers on the Data & Analytics team who are hiring summer interns. We finalize our postings for the three types of positions (Open Data Associate, Data Science Associate, and Data Engineering Associate). Interns create a core part of our team’s capacity and the work they do gets put into production-grade pipelines and datasets.
1:00 p.m.
Lunch time! Today I’ve brought a sandwich and fruit from home (thrilling content, I know!).
2:00 p.m.
The afternoon meeting marathon begins. First on deck this afternoon is a meeting with my team to finalize presentation materials for NYC Open Data Week (March 16-24). Our team is planning to lead a couple events and publish multiple resources in March as part of the festivities. We love the celebratory spirit of the week and enjoy the increased interaction with stakeholders! Stay tuned for extra blog posts this month in honor of NYC Open Data Week.
Immediately following the meeting with my team, I meet with my boss, Andy Kuziemko, one on one to prioritize tasks for the upcoming sprint. It is an incredibly busy month, and these meetings help us set realistic expectations around deadlines for all the stakeholders who depend on our data.
For my last meeting of the day, I meet with a new data analyst in another part of the organization who wants to learn more about the MTA’s Open Data program. Conversations like these are a great reminder that there is always more internal outreach to do around Open Data and how our program is such a critical player in the internal data ecosystem!
5:00 p.m.
As a follow-up to the meeting with my boss, I take some time to create new tickets in Gitlab for work that needs to get done in the upcoming sprint.
5:45 p.m.
And, with the tickets created and a couple more emails sent, I call it a day at the office. I grab a Citi Bike and head home for the evening, ready to relax, recharge and do it all again tomorrow.
About the author
Lisa Mae Fiedler manages the MTA’s Open Data program. You can check out the MTA’s open datasets by visiting data.ny.gov.
Want to be a summer intern on the Data & Analytics team? View the job postings here (Open Data Associate, Data Science Associate, and Data Engineering Associate) and apply by emailing your resume, following the instructions on each respective posting.