Hey there. My name is James Gilson. Despite the difficulties imposed by the pandemic over the last year, I have managed to transition into exactly the kind of role I envisioned for myself when beginning my tenure at Columbia—and I want to share my experience.
But first, a bit about me. I studied psychology and economics as an undergraduate, after which, I began my career as a consumer researcher at a large consulting firm. Starting out in a larger company with lots of organizational structure, support systems, well-defined development goals, and ample mentorship opportunities provided a great setting for my first foray into the professional world. I quickly developed the time management, communication, and organizational skills fundamental for success in any workplace.
As I continued to advance in my career and the role, however, I started to feel pigeonholed by the lack of flexibility. Much of the work on projects I led that I found most interesting was outsourced internally to specialized teams. I eventually determined that in order to continue developing, I needed a stronger foundation in technical skills.
This ultimately led me to the Applied Analytics M.S. program at Columbia, which gave me the opportunity to equip myself with all the tools necessary to make this pivot. I graduated from the program in December 2019. While I enjoyed all the classes I took, the SQL and Data Modeling electives (taught by Nick Machairas and Steve Hoberman, respectively) were particularly useful in providing the context necessary for professional success. On top of the skills I developed from the coursework, my transition from academia back to industry was assisted by the support I received from the Career Design Lab. The CDL team helped to ensure I presented myself in the best possible way to recruiters, organized numerous job fairs where I directly engaged with employers, and connected me with a powerful network through which I scored an internship and gained critical hands-on experience.
Ultimately, I landed a position at GrowthLoop, a marketing technology start-up developing a SAAS product to make data warehouses accessible to business teams (we’re hiring, by the way). While my official job title is Data Analyst, the flexibility afforded by working on a smaller team has meant that my day-to-day usually spans a variety of different areas. On any given day, my responsibilities may encompass technical tasks involving data engineering; data modeling; predictive modeling and data integrations with our software product; consulting-oriented tasks, such as client-facing presentations and general relationship management; and internal priorities, like operational process improvements and higher-level strategic business initiatives.
Working on a small and dynamic team has made work more challenging, but also so much more interesting and engaging. Here’s a sample of a day in my life at GrowthLoop.
Morning Routine
I generally start my day making coffee and taking a walk around the neighborhood. I’ve enjoyed the perks of the remote work lifestyle, but I do look forward to getting back into the office, at least for a few days a week. In the meantime, I make a point to take some personal time in the morning prior to sitting down at my desk. Because many of the folks on our team are on Pacific Time, I generally have my first few hours blocked for deep work—tasks I can handle on my own that benefit from a lack of distractions.
Stand-Up
Once the Slack messages start pinging around 11 a.m., I take some time to prioritize my day at a high level. Every day around this time, our Analytics/Data Science team hops on a stand-up to run through our individual priorities. The stand-up keeps us up-to-date on what we’re all working on and allows us to share knowledge and get involved in each other’s work. This has been an especially important way to gather as a team while we’re all working remotely.
Data Modeling & Predictive Modeling
I generally spend a few hours a day focused on building out and maintaining data models. From the high-level concepts all the way down to the infrastructure and code that executes our ETL pipelines, it’s these data structures and transformations that enable the higher-level analytics that we ultimately strive for. Most recently, I’ve been working on designing and implementing the data structures that will enable streaming ML pipelines for one of our enterprise clients.
Pair Programming & Analysis
Having smart and talented colleagues is a huge perk to the job, and I try to spend as much time learning from them as possible. I try to pair often to walk through code I’ve written or analysis I’m getting ready to present to a client. I’ve found that pairing with colleagues who specialize in different areas, like those who are more engineering-focused, is a great way to fill in the gaps in my knowledge and keep growing.
Client Meeting & Presentation
Managing relationships with our clients is another important part of my job. Afternoons often involve preparing for weekly client calls. Some of the most rewarding moments for me come from working hard to deliver something and having it received well. Being able to take a project from ideation and data modeling all the way to a presentation of outcomes makes it that much better.
World’s Fair
Every week, we have an all-hands meeting that we affectionately call the GrowthLoop World’s Fair. We use this time to come together and show off the cool stuff we’ve been working on to one another. These meetings create a sense of community at GrowthLoop, and in addition to all the banter, they give us an opportunity to reflect on what we’ve accomplished so far and align where we’re going—two things that I think are absolutely vital for long-term success in any workplace.
I hope my experience of life after graduate school is helpful in envisioning your own path. Don’t hesitate to reach out at james [[at]] growthloop [[dot]] com (james[at]growthloop[dot]com) if you’d like to connect!
The views expressed are those of the author and do not necessarily represent the views of any other person or entity.
