Zero Coding to Senior Data Scientist in 4 Years

My journey so far in finding a purpose in my craft

I already have a short “About Me” story published, but this is meant to more extensively and transparently discuss my journey in how I became a Senior Data Scientist from nothing. My story starts at what was a hard rock bottom at the time and now I get to work on fascinating end-to-end machine learning problems.

My Data Science journey is not at all a traditional one. The last 5 years have been a wild ride, but there are pieces from my story that I believe others can learn from. The main reason for me sharing this is to give a better glimpse into who I am and where I come from with the hopes that it may inspire others out there to carve their own path.

My career story starts at rock bottom, failing hard at the one thing I thought I wanted to do.

Road to the Bottom

My undergraduate years at Wayne State University were primarily spent pursuing Pre-Medicine as I aspired to become a physician. The field that interested me most was Neuroscience because I was fascinated with how the brain works and understanding the psychology behind human behaviors. Alongside my science-heavy curriculum, I majored in Philosophy mainly because I was just interested in it. It was one of those subjects where classes felt more like “fun” than “school” for me. Classes like Philosophy of the Mind, Philosophy of Science, and Metaphysics were some of my favorite.

The science classes were intriguing to me, I loved learning most of what I was studying but I knew I learned better with hands-on work. As I started my upperclassmen years, I started doing research at a Neuroscience Psychiatry Lab on Wayne Medical Campus. The lab received fMRI brain scans from clinical trials and we were tasked to analyze the brain images in MATLAB and write up papers and give presentations for national conferences for brain, behavior, and psychiatry illnesses.

Although I was doing quite a bit, I knew my potential was not tapped into these years. I was smart enough to get decent grades in my classes, but not smart enough to ace every exam. This enabled me to do the worst thing I could have done: never really stop and question what I truly enjoyed learning and why.

The hard wall hit my life when I was studying for the MCAT. 6 months of studying as hard as I knew how to at the time (this was right before they changed the exam to the new scoring format), I was nearly a zombie when I took it. Regardless, I felt pretty good about the content I was tested on. The scores disagreed. The exam was out of 36, 27–29 was decent, 30–32 was pretty good, 32–34 was very good, 35–36 was insane. The first practice exam I took before my 6 months started I scored a 22 and that is also the first official score I got. Absolutely crushing.

It’s looked unfavorable to retake the MCAT, but even worse to retake and get an even lower score. I thought that couldn’t be possible, right? I muster up the energy and courage to retake it one last time before the exam completely changed, the very last exam I’d give. Much healthier, physically and mentally, this time around. My mind was sharp and I was ready. I take the second exam 1 month later and I get a 21. Instantly went from crushed to broken.

Medicine was all I believed I wanted to do. It was the path I claimed for myself and now I’m graduating with a Philosophy major trying to figure out what I can even do with the skills I have. Maybe Pharmacy? I have the science credits. Maybe Computer Science? It would be another 4 years, but I enjoy Technology. Nothing seemed to stick because my mind was still reeling from the crushing failure I experienced.

My dad was a highly proficient DBA Tech Lead at the time and saved me from this dark time. He said, “Teach yourself SQL and do some freelance work with me”. I didn’t know at all what I was learning, but I knew I needed something new. Medicine wasn’t for me and I wanted to create, innovate, and build. I left the research lab soon after, ready to take the plunge into an entirely new world.

I left the research lab soon after, ready to take the plunge into an entirely new world.

The Graciousness of Good People

The one good thing about rock bottom is that any move feels like progress. And if you can fill those moments with deep gratitude for those around you, then it can almost feel euphoric.

The one good thing about rock bottom is that any move feels like progress. And if you can fill those moments with deep gratitude for those around you, then it can almost feel euphoric.

I started learning SQL heavily for 1 year and started applying for Data Analyst roles. Keep in mind, I have no clue what I’m doing but I know I’m ready to take on any new challenge. After numerous failed interviews, the good people at Jackson National Life took me in. The interview went so well the hiring manager gave me the position on the walk out of the interview. I asked him years later why he did that for a kid with no real credentials or experience, he said, “I just saw something in you that told me you were going to go really far. In fact, I knew it in the first 5 minutes”.

I never understood what he meant by that, but I knew how immensely grateful I was for the Jackson team to take me in. I let my gratitude for the strong leaders there fuel my drive to do great work for them. I met one of my closest friends on the first team I joined as well; he was the team lead of the Metrics & Forecasting team and I was the newbie. He introduced me to the corporate world by showing me that walking over to check in on coworkers was much more effective and kind than just emailing, “When can I get this by?”. He showed me that spending time laughing with and helping those around you, especially when it’s not in your job description, makes for genuine relationships that last forever. It’s been 4–5 years since I’ve worked on his team, but I still try to emulate his leadership every day.

Within one year at Jackson, I became highly skilled at Tableau and Data Analysis and was striving to reach the next height. Right at this time, my company hosted an enterprise-wide data analytics & science competition. Teams of 10 business leaders, technical artists, and data professionals came together to innovate and kickstart the company’s data transformation. The same manager who believed in me nominated me to participate in this competition — a kid with 2 years joining in the ring with the average being closer to 10 years at the company. Although I learned a lot and even was chosen to present our final presentation to the senior executive team, our team got crushed. I deeply felt the gap between where my skills were and where I wanted them to be.

After a bit of googling, I saw the term Data Scientist for the first time and it felt like exactly the work I wanted to do. I couldn’t stop reading — I wanted to know everything about what people in this field did, how they got there, how to be good at it, everything. I knew I’d need more structure to learn it well and I started looking up Masters programs within a month. My luck seemed to be striking because a top University in my state at the time, the University of Michigan, just launched a fully accredited, fully online Masters in Applied Data Science (MADS) program.

Chasing Mastery

The curriculum of the MADS program was exactly what I was looking for — extensive, end-to-end Data Science classes ranging from Being a Data Scientist to Information Visualization to Causal Inference to Machine Learning and so much more. Also being a top research institution I knew I wanted to participate in cutting-edge machine learning projects alongside some of the brightest and ambitious students that UMich is known for. The only issue? Entrance required passing standardized tests in Statistics (which I knew relatively well) and Python (which I did not know of at the time).

Starting then, I worked harder than I knew I was capable of. I was not going to let this be a repeat of what had occurred with the MCAT just a few years prior. I finished a Python 3 Specialization on Coursera, a series of 5 courses, and the Khan Academy Statistics and Probability track in 2 months each, completing every single exercise problem and persistently practicing mastery learning every day. I thought I had shattered my limits for learning this year, but after enrolling in the first cohort class of 2020 I achieved heights I never knew I was capable of.

In 2 years of working full time and school full time, I took on research projects on the side to do Computer Vision on paintings which ended up as an exhibit in a Museum, analyzed NBA games with graphs to create a new metric to measure performance and strategy, participated in various competitions such as a biomechanics one for improving physiotherapy, was an instructional aide for Causal Inference, was on the Student Leadership Board, and attempted to assist national law enforcement for tackling global wildlife trafficking with machine learning. All of this was done with the help of some deeply inspiring and helpful students, faculty, and mentors that guided me along the way.

Meanwhile, at work, I had moved from being a Data Analyst to a Data Scientist/Engineer working on enterprise machine learning problems while leading the Data Science & AI Community of Practice alongside ambitious coworkers who soon turned into cherished friends. About halfway through 2020, I took on writing to expand my repertoire and establish a broader brand for myself. This led to new projects exploring complex concepts applied in domains I’m passionate about (Applied Bayesian Inference, Graph Machine Learning, TensorFlow, etc.). In 6 months, I wrote greater than 12 pieces and was featured in the top Data Science publication, Towards Data Science, nearly every time.

By the end of 2020, a boutique consulting firm Fulcrum Analytics took notice of me due to my writing (which included code, concepts, and inference) and saw I was fit for a Senior Data Scientist role. They talked to me at length about the depths of the unique projects I’ve had the chance to work on, but loved how laser-focused I was in providing value for people — a balance crucial for technical consultants. It was hard to grasp at first; the job I had deeply wanted and the craft that I found a new passion in was offered to me at a Senior level in a city I’d dreamed about living in (New York) soon after graduating from a Masters program.

It was hard to grasp at first; the job I had deeply wanted and the craft that I found a new passion in was offered to me at a Senior level in a city I’d dreamed about living in (New York) soon after graduating from a Masters program.

Now I work with clients to help them with building enterprise machine learning systems across healthcare, financial services, and retail industries. The role involves a strong balance between people and technology working on challenging data problems.

Giving Back to the Community

The countless hours I spent getting to know people and working on projects I was so inspired by paid off massively, but honestly, that’s not why I did any of it. I found a world of wonder learning Data Science and Machine Learning coming from absolutely nothing that I hope to inspire and instill in anyone who reads my content. It’s the core reason why I try to write and teach what I know — to lift others up and help them see the wonder in their lives. What do I mean by this? How can “a job” be wondrous?

I’m not talking about the title “Data Scientist” being full of wonder, I’m talking about what having those skills does to problems around you. I care a lot about the environment, sports, and health but I did not have a great way of tangibly working on solutions to problems in those spaces. And even if I did, there was no guarantee to work on things that could make a difference. This field is by design creative, challenging, collaborative, and high value/impact. Learning data skills is not important so you can have a data job; it’s important so you can solve critical, significant problems you care about.

Learning data skills is not important so you can have a data job; it’s important so you can solve critical, significant problems you care about.

My story is filled with hard work, but I’m the first to admit how impactful gracious mentors were in shaping my story. Although I have a long way to go and a lot to learn still, if there are aspiring Data Scientists or Machine Learning Engineers (or current ones) that want to connect I’d be honored to meet and discuss with learners out there. I’m a storyteller at heart and hearing your story is important to me, especially if you stuck around this long reading mine.

Feel free to reach out via LinkedIn or Twitter and we can set up a meeting to chat — looking forward to meeting more in the community!