From Academia to Data Science: A Story of My Career Journey So Far
I have an unusual journey when it comes to being a data scientist …at least I used to think so. Here is my story.
I originally posted this on my original blog. At the tail end of 2022, I made a goal to post more regularly, and so I started a new blog here on Substack. In this newsletter, Step Up Step Together, I will share reflections and advice on personal and professional development to enable individual and organizational transformation based on my experiences as a social psychologist and data scientist, which I describe below.
I am a data scientist.
And a social scientist. And a mother. And an Asian American Arizonan. And sometimes an artist. But that’s all neither here nor there (sort of).
The point is, I have an unusual journey when it comes to being a data scientist …at least I used to think so. Now, after having met many data scientists, I see how everyone’s journey is the same in that everyone’s journey is different.
This is partly due to the variable nature of data science (are we talking about analytics, machine learning, statistics, visualizations, data queries, engineering, or everything in between?). And people can become data scientists from almost any which direction.
It’s also partly because, whether they’re a data scientist or not, everyone has a different and valuable story to tell that is shaped by their own mix of experiences and reactions to events.
I remind myself of this when I start to lose my nerve to share my story, and a question from a dark space in my brain creeps out to ask – would anyone really care about what I have to say? I used to answer, “Well, maybe?”, then my fear of the worst reaction I could get would stop me from hitting submit.
Everyone has a story to tell
Now, I like to think about how every person’s experience, even mine, represents a unique data point, and the beauty in sharing one’s individual story is that it can be pooled together with other data points to reveal patterns about the bigger picture. Through interpreting what that bigger picture means, we learn new lessons and forge new stories both individually and collectively, and the cycle starts again.
So here I am, sharing my version of my story as I understand it at this point in time. My hope is it can give you a useful data point, whether you’re considering a data science career, you’re a data scientist looking to understand your own journey or you’re not a data scientist at all but you’re interested in another person’s journey through this thing called “life”. (I hear this famous lyric as it’s said in the movie Sing 2. I have two kids under 5. I can’t get these songs out of my head, and I’m not going to fight it.)
If you’re looking for a nuts and bolts “how to prepare for data science” post, look to other great resources, like this, this, this, and this. My post will focus on the human experience of what it’s like to navigate a career change, shove down imposter syndrome while faking it ‘til you make it, and learn a new set of hard skills (and I’m not just talking about coding and machine learning).
You ready? Let’s go!
Academia and Love of Research
When I was in college, data science didn’t exist, at least not in the form it is in today.
What did exist was a website called TheFacebook that had just popped up and spread like wildfire through the campus. Status updates were casual and frequent, poking was the most popular way to say “hi”, and the Like button was not even a twinkle in someone’s eye.
What also existed was me, a psychology major who had fallen in love with social science research. I worked in labs where we collected data through hypothesis-driven social experiments inside small rooms down narrow halls of the psychology building. As a research assistant, I painstakingly typed thousands of paper-pencil survey responses into thick white iMacs. For many people, working in spreadsheets for hours would be mind-numbing misery. Not for me!
I loved seeing how individuals responded to a situation we set up for them, how those individual responses could be captured as measurable quantities, and then how those quantified responses could be grouped together to tell us something about what it means to be human. I saw research as a beautiful, almost magical, process of going back and forth between the immeasurable and measurable. I followed this love for research, data, and – yes, I’ll admit it – spreadsheets to graduate school, and I earned a PhD in social psychology from Stanford.
Despite being a born academic headed straight toward the tenured professor path, in my last year of grad school, I took a sharp left turn and explored becoming a data scientist in industry. Having been in Silicon Valley for nearly a decade when data science was taking off as the most promising career according to LinkedIn, I watched the chocolate factory rise up around me and a golden ticket dangled in my reach. I was torn between taking a chance to go for that ticket and win an opportunity of a lifetime or continuing down a path whose milestones were clear and I knew how I fit in.
Breaking into Data Science
For most psychologists, despite being experts in creating quantitative social experiments and using sophisticated statistical analyses, data science jobs felt inaccessible because psychologists mostly analyzed data using point-and-click programs, not coding. Lucky for me, in grad school, I was in the first cohort where the statistics courses were taught using the statistical coding language,R(thank you Ewart). I was hooked on coding from the first time I typedprint("Hello World!"). I would spend countless hours debugging code and running headlong into intoxicating rabbit holes like how to format my output so my assignments would print pretty.
When data science came into my sights, I had two reactions. First, the self-doubt and imposter syndrome was strong with me. Data science seemed like a field for engineers or physicists, not for a squishy social scientist like me. By the way, social scientists are anything but squishy, and if they are, it’s because being human is squishy. In either case, my amygdala screamed – Warning! Warning! YOU CAN’T DO THIS. Abort! Turn back!
Then, once the alarm bells subsided, I was able to see that there was something deeper inside me, hidden beneath the heavy doubts and loud fears, that burned small and bright with the conviction that my skills, experiences, and interests set me up well for a domain that combined data, analysis, and business insights. A quiet voice, close to my heart, whispered – I want to do it and I CAN do it, if I just put myself out there.
So that’s what I did. I applied to a few positions, got a few interviews …and failed immediately.
After licking my wounds, I started to teach myself Python and how to access New York Times data through APIs. A friend told me about a fellowship called Insight Data Science that helped PhDs transition to data science jobs in industry and happened to be located a mile from my apartment in Palo Alto. I couldn’t ignore the Universe pointing big arrow signs inviting me to my next big adventure. I applied to the program, and using my ability to tell compelling data stories, I was accepted.
After I completed the program, I was poised to jump into the data science job market. Before I could start, Insight offered me a job to work with them as a data science program director. It was a role that would allow me to continue gaining data science experience and network with data science leaders while also capitalize on my passion for mentorship through training budding data scientists who would themselves turn into data science leaders. (For examples of data science projects that fellows completed during the program using open-source data, see here.) I accepted the role, and the dirt path I had stepped onto when I decided to go into data science turned to road under my feet.
Working in Data Science: A Brief Summary
After Insight, I worked as a data scientist at Twitter and later as a data science manager at Facebook, which became Meta last year. I’ve worked with Sales Finance teams to train revenue forecasting models, teach finance analysts how to use R, and translate data insights for the CFO; with Product Analytics to track, understand and report on topline metrics; and with Marketing to perform analyses and design measurement of marketing campaigns so that we could better understand consumer behavior and sentiment.
Across all these experiences, the standout moments are the ones where I worked with others. I loved spending time with my team and supporting them to be their best selves so that they could find a way to do work that was not only challenging and impactful but also fulfilling. I smile when I think about the incredibly smart and warm colleagues I worked with over the years. I may not remember any more what the exact problems were that we were trying to solve, but I hold close to the memories of our meetings that were filled with laughter, shared frustration, deep thinking, and innovative solutions.
Reflections: From “Getting it Right” to Embracing the Unknown
When I was a psychology major in college, I never would have predicted this is where my journey would take me. As I look back, I appreciate the opportunities that came my way and that when those opportunities came, I was prepared to reach for them and sometimes even catch them.
I’ve been reflecting on the lessons I’ve learned across this journey, what behaviors and tendencies I want to take with me going forward and which ones I want to change. I’ve realized that for much of my life, whether I was transitioning to a new role or working in academia or industry, I’ve chased after what I thought was the right thing to do. For the most part that worked for me, and I’ve been happy, fulfilled, and successful. Sometimes I even felt like I was making it while faking it.
Then, not too long ago, my drive to “get it right” broke down for me when faced with a series of challenging work experiences, ones I’d never encountered before. In the past, I had been able to fight my way through the pressures of grad school or imposter syndrome when transitioning to data science by throwing everything I could at “getting it right”. In this situation, however, I hit a wall. Despite the vast amount of energy I spent trying to do my best, I fell into uncontrollable depression when I thought I failed and heart-gripping anxiety when I tried to prevent myself from failing in the future.
I was lucky in this situation to have had many resources, really lifelines, available to me. I found support in a leadership group based on the book, The 15 Commitments of Conscious Leadership (a must read for anyone looking to live not only a successful life but a fully alive one). I worked with a professional coach and later a therapist. I had friends and colleagues who patiently listened to me when I dumped all my big feelings on them. Combined together, all these folks showed me in their own ways that in order to find peace with myself, I would need to release my grip on wanting to be right and trying to control what other people thought of me. I plumbed deep into ugly and cathartic self-exploration to understand what that advice meant for me. I have emerged feeling like I have some tools I can use to practice identifying my inner truth, putting my best self forward and embracing the unknown of whatever could come back and what I can learn from it.
Now I’m at another crossroads where I don’t know what the future will hold. I couldn’t have learned these lessons to let go of “getting it right” and embrace the unknown at a better time. Past me would be doing everything she could to bury fear and apprehension in order to move forward with a brave and sometimes faltering face. Instead, I am taking a deep breath. My heart is quiet and calm, my eyes are open and clear, and I’m excited to see where my journey will take me next.
Your Turn
Whew! So there you have it, another person’s story, a small slice of my journey so far. Now I want to know – what’s yours?
Thank you to Katie Amrine, Emily Thompson, and Emily Whitmore for their encouragement and advice on sharing my story.