As I lie in bed chugging NyQuil and sipping piping hot tea to recover from this awful cold I caught on my recent trip to San Francisco, I figured what better way to start the new year than to document the journey that’s to come. But since this is my first ever post, here’s a little bit about me.
I graduated with a Master’s in Quantitative Finance from MIT in June 2017. Prior to that, I studied Economics and Mathematics as an undergraduate at Cornell University. Up until a couple of months ago, I was a quantitative risk analyst at the world’s largest asset management firm. With over $40 billion worth of assets under management in just the firm’s high yield fixed income business alone, I risk-managed our portfolios using a combination of R, SQL, and the firm’s proprietary risk management platform to pull, manipulate, and process large datasets of over 125,000 individual securities to address the real-time information needs of senior portfolio managers.
I am incredibly grateful for the year and a half I spent honing not just my quantitative skills with some of the brightest people in the industry, but also learning how to handle some of the most demanding individuals I’ve ever met. However, in time I realized I wouldn’t be able to grow any further with the team I was on as the opportunities to expand beyond my current duties were limited. Since my department had a rather strict time frame against internal mobility without a guarantee that a transfer would even be granted, I decided it was time for a move.
Though I believe my academic background and professional experiences demonstrate the mathematical and statistical competence required to transition into a career as a data scientist, my project portfolio was pretty much non-existent as the nature of day-to-day work did not allow enough leeway to work on data science projects.
While my Master’s at MIT introduced to basic machine learning concepts such as ridge and lasso regressions, and tree-based methods such as random forests and bagging, I lacked significant depth. As a result, I came to the conclusion that dedicating 100% of my time to an immersive data science boot camp would give me the time, opportunities, and mentorship that I need to fill in the missing gaps to make a successful career change.
Of course, it was a huge risk — some might say it is almost ironic actually as a (former) risk manager — to leave a stable job. But as the basics of investing dictate: in order to expect favorable returns on a decision, you have to take risks. A savvy investor manages risk not just by being cognizant of its existence, but also gauging how much is present in any given investment and assessing his/her capacity to handle said risk. That being said, this is a carefully calculated risk that I’m taking, not a blind gamble.
I know there are a lot of people out there who are looking to make a similar career change so I’m hoping this blog will be somewhat inspirational. I’ll be documenting my journey, sharing my thoughts on readings that I come across, and making concepts easy to digest to the hopeful data scientist.
Well 2018, it’s been a wild ride, but it’s time for something change. As Franz Kafka wisely said, “From a certain point onward there is no longer any turning back. That is the point that must be reached”. Happy New Year!