The Advice that Started my Career in Data Science
With one semester left of my statistics degree and two and half years after becoming a research assistant, I formulated a plan to become a data scientist.
“It had finally occurred to me that data science was the avenue by which I could give back to humankind. I could leverage my solid foundation in statistics and experience coding in R and python, to join an interdisciplinary field that was breaking ground in biosciences and beyond.”
A Golden Opportunity
In late June of this year, in the midst of an intensely busy and challenging module of the MBusA, my brother messaged me about a data science position at a biotech software startup. I looked into it and the job description immediately grabbed my interest.
This job advertisement, and this company, appeared different.
The job listed a set of interests like machine learning, graph theory and bioscience as well as attitudes like radical honesty and customer centric design. I’d been doing lots of machine learning recently, had applied graph theory in my computational biology major and was keen to apply all the bioscience that had been accumulating dust in my head.
So I decided to go for it. And I mean GO FOR IT. By the end of the final job interview round, I think I’d written about 20k words. Words I’d written summarising the background of the founders, looking at articles about start-ups, researching product development, summarising old projects or relevant studies so I could sell myself.
Success and a Challenge
In the end, I was offered the position of data scientist at Mass Dynamics.
With 8 weeks of coursework and a similar length internship left on my masters, I’m not sure I even considered finishing. This felt like my chance.
“In the words of Alexander Hamilton as relayed by Lin-Manuel Miranda — “I am not throwin’ away my shot”
Two weeks in, being part of Mass Dynamics has met and exceeded my expectations. I love getting to work closely with passionate, talented people.
I feel like I’m learning more in weeks than I learnt in months while studying, but that doesn’t mean I’m not using my previous studies. If anything, I feel like I never know which prior experience, from data science, computational biology or even biochemistry is going to help contribute to the next challenge.
Mass Dynamics is on a mission to accelerate medical breakthroughs by making it easier to derive insights from scientific data. We’re building an ecosystem for the analysis of scientific data that is founded jointly on solid software engineering principles, scientific expertise and human-centred design.
The best part is that despite giving up on my dream of becoming a life scientist I still get to help accelerate breakthroughs that will help humanity which was always the whole point anyway!
But getting over the fact that this new position and my new workplace are awesome, I have also internalised that it is a challenge and a responsibility. Mass Dynamics have given me my shot and I intend to take it.
Advice and Tips
So what is the lesson? What is the takeaway?
- Never stop learning. Never stop asking questions. In the long run, it’s how fast you learn not where you started or where you are right now that will matter.
- Be resilient. Failure is a learning experience.
- It’s not a 0 sum game. Life isn’t a Kaggle competition. Learn from others, share what you can.
- Find valuable mentors. I owe so much, maybe everything, to the people who listened and especially the people who told me to shut up and told me what’s what.
I never doubted it, but this year, it seems especially obvious that humankind needs excellence in biotech to protect ourselves and create a brighter future. Once upon a time, I thought the only way I could do this was a researcher. Now, I think that if you want to help, you can find a way.
Look to those around you, ask what they think and really listen.