Data-driven dreams, realized

Becoming a data scientist was no straight path, and if I were to tell my college freshman year self that this would be my occupation, I would not have believed it. I went into the University of Southern California as a Business Administration major, with the intent of finding my landing spot somewhere in finance or consulting. By my sophomore year, I became laser focused on pursuing accounting as I was definitely drinking the kool-aid of one of the most charismatic professors on campus. After taking some of the harder accounting classes, I realized it was not for me. Luckily, after sophomore year I did an internship at a litigation firm that specialized in statistical analyses where they taught us how to code with SAS. That was the very first time I had done any sort of coding, and it was not what I expected — I actually liked it!

The idea of pursuing data science grew on me from that experience, so when I entered my junior year I switched to a Data Sciences & Operations emphasis (still in the business school) and added on an Applied Analytics minor. I was also interested in new coding languages so I took Python and Web Publishing which taught HTML and CSS. My grades were pretty average throughout college, but I do remember that I got a 100% on my statistics final which was a good cue that I was heading in the right direction.

When it came around the time to apply for internships my Junior year, I was getting frustrated by how competitive they were. I recall applying to hundreds of internships and not landing any of them. It was approaching the end of the year when I finally landed an interview and it was at Amazon! I had not even remembered applying, but was ecstatic. There was a lot of pressure during the interview process, and the preparation consumed my life for a while. I thought I ruined my chances during the third round when I booked a conference room in the business building and the wifi was not working, so I missed the recruiter’s call. Luckily, they rescheduled and I moved onto the final round. I got my Business Analyst internship offer at the very beginning of May and was so relieved, excited, and nervous! This would mean I would be moving to Seattle for the entire summer, and have my first experience working at a Big Tech and FAANG company.

The summer of my internship was definitely a memorable one, where I had to learn to sink or swim in an ambiguous environment. I was placed in AWS Infrastructure as a Business Analyst intern, where I came into it knowing absolutely nothing about the cloud, infrastructure planning, or how scrappy and fast-faced things could be. But, I came out of it with my future roommate and best friend, many learnings, and the golden ticket to a full time position the following summer.

I finished my senior year at USC taking classes I was highly interested in to accelerate my skillset building. I even emailed the head of a USC graduate program and asked if I could sit in on a few graduate-level machine learning courses, where I received a 2-letter “ok.” in response to my page-long lengthy plea. Most of my Data Sciences & Operations classes were focused on SQL, and Applied Analytics classes on machine learning in R.

One thing that was still apparent was the lack of gender diversity in some of the classes. I had gotten pretty good at SQL and recall my professor hosting a few competitions on who got the correct query first, and upon heading to the front of the class to collect my prize I instead got a puzzled look and questioning as to what I was doing up there (some foreshadowing to experiences of working in the tech industry). Prior to graduating, my internship manager reached out to me via LinkedIn letting me know that my internship project was being turned into a product — this was extremely thrilling for me, and some much needed validation that I had at least done something right (Devil Wears Prada reference, lol).

I graduated from USC in 2018 and had a very short Eurotrip with my sister before packing up my life in LA and moving to Seattle. I returned full-time as a Business Analyst, and was the first person on the newly formed Infrastructure Decision Science team. For an entry-level position, I gained incredible experience interacting with senior executives — even regularly presenting to them and preparing updates to Andy Jassy. This role is where I truly learned the art of developing metrics, automated dashboards, and business review decks. I like to think that it also conditioned me to start reading the minds of executives and anticipating questions asked. I transitioned into developing a statistical modeling tool, being able to leverage my data science, R, and Python skills in addition to SQL and dashboards (note — people rarely use R in tech; I suggest only taking SQL and Python classes in college). I was able to get many high impact projects under my belt, and promoted quickly within one year.

The thing that really chipped away at my empath self during that time was the lack of diversity, specifically in the Infrastructure environment. I recall many moments of sobbing quietly at my desk staring at my org chart where every single leader in the chain was male — and nothing had changed over the course of a whole year. With every new re-org or promotion announcement I would have a slight glimmer of hope, to only be disappointed yet again. When I reflect back on that time, I have sympathy that I felt such a deep sense of injustice. However, I was beating a dead horse trying to create change when it would never be a priority. Simply existing in that environment was enough, and I know that now. My two cents is to contribute to DE&I only where it is welcomed, encouraged, and part of the org’s strategy!

After having a large data science project as well as several BI projects under my belt, I felt a deep desire to transition from a Business Analyst to a Data Scientist role. This is a very rare leap to make as in most cases — you normally need to first move to a Business Intelligence Engineer role prior to a Data Scientist role (at least at Amazon). I started interviewing with internal teams and was told no repeatedly or ghosted. What you must know by now is that I do not take no for an answer, am a bit delulu (in Gen Z terms), and am always looking to make the impossible happen.

My previous director had moved to a new team, and let me know about a role opening. I convinced the hiring manager to convert the role from a Data Engineer to a Data Scientist role based on project needs, but I still had to go through the tech assessment to change job families. I went through the behavioral loop, and was notified that I had been assigned a Senior Applied Scientist manager for my assessment. I was sweating bullets as that was probably the most challenging assignment I could have received — luckily, I was able to get through all the technical SQL, Python, and ML questions and passed!

Actually getting the data science role is a feat in itself (especially with a job family change), but being in-role is a beast of its own. As you may have read in my data job families blog, job titles can be very loose in terms of responsibilities. Though I had finally achieved my dream title, the work I did was a bit all over the place with data pipelines, dashboards, business reviews, product requirements, and Python prototyping. I was appreciative that I got experience being the sole technical owner across various teams — but was definitely spreading myself thin. I was put on a project during COVID in addition to my full-time role supporting multiple teams, and probably slept 3-4 hours a night for several months. To add to the sleep-deprived frustration, I was on a promotion slate within a year and a half of starting the role with many high visibility projects — but my machine learning portfolio was lacking from the core needs of the team.

As a lifeling perfectionist and participant of team no sleep (pulling all nighters as far back as middle school), burnout snuck up on me and snatched away everything I had worked so hard for. I do not blame anyone I worked with for what happened to me, which was hard to see clearly in the moment. I never learned how to say no, communicate limited bandwidth, or set boundaries with my schedule. I had always pushed myself hard to make the impossible happen, but I started slipping with my work output and my health started quickly deteriorating. I moved back to LA in late 2020, which definitely helped with having my support system of friends and family in close proximity. However, I kept trying to sustain the insane work schedule I had upkept for so long and it got to the point where my nervous system was shot, I was crying nonstop daily, and was no longer able to do basic daily tasks. My sister gave me a much needed reality check, and I took a 3-month medical leave.

My sabbatical was one of the best things that could have happened to me, as I was able to completely reset my daily routine and heal my nervous system. During this time I was really able to think about what I wanted my life to look like outside of work — and voila! this blog was born. I started going to sound baths every week, took up French classes, and embarked on my Sommelier journey. I was feeling so much better upon returning, only to be thrown back into the fire and harrassed daily by toxic newly hired employees and a partner manager. I knew they would remain protected despite countless complaints, so I immediately interviewed for a new role. I am grateful for the many co-workers who checked-in on me frequently and validated that the treatment I received was not okay.

I was shortly offered a role in Talent Acquisition, which I was very excited about. However, I was placed on a different sub-team than what I had originally interviewed for at the last minute. I tested it out for a month, but came to the conclusion that the role did not require data science skills and I already learned the hard way that it is better to leave immediately rather than stay in a role that is out of alignment of your career goals. An old manager of mine had an open role on the .com side, and I was ecstatic to accept the role. I finally fulfilled my dream of working on machine learning models, production environments, and seeing it come to life on the Amazon website.

This role also challenged me the most, as my team members were much more technical than I was. I definitely felt a huge amount of imposter syndrome, but I am very proud of the machine learning and MLOps work that I did do. This team comprised of some of my favorite teammates I had ever worked with, and I was pushed to develop my technical skills in a way I never had the opportunity to in previous roles (note - true data science teams are hard to come by, do your research prior to interviewing). This is where I reference my lessons in tech blog, where sometimes you have to do the challenging role to get to your dream role. Towards the latter end of my time on the team, I was re-orged to a software team. Here I learned much more about software engineering concepts, agile planning, and building technical products. This definitely became a new passion for me, and I decided it was time for me to pivot to a Technical Program Manager (TPM) role - and to my surprise, others saw that change for me as well!

And that leads me to my updated segment of this blog where I have now pivoted to a Principal TPM role (though I still use data science skills in-role). After the promotion dead-end in my first Data Scientist role, and a handful of manager changes thereafter inhibiting a realistic promotion track, I decided my time at Amazon needed to come to an end. I at least had enough senior-level work on my resume to apply for a Principal TPM role (but, I had to ask for it - always ask!). I created a full circle moment by going back to cloud infrastructure externally, and am able to approach it with radical acceptance of the environment that I signed up for. Diversity contributions come in all forms, and sometimes it can be a side-project rather than an expectation from your full-time role. Now, I am able to focus on working on projects that truly align to my career goals, push me into fast growth mode, build my business and technical skillsets, and focus on prioritization of tasks. It has been a wild ride, but I would not change any of it! I am deeply grateful for all leaders, managers, and co-workers that helped to pave the path for my journey today.

XX Nicole

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