Hello. I’m Alok.

The facts: I’m Head of Data Science & Machine Learning at DoorDash. Previously I was Senior Director of Data Science at Lyft, and before that a Director of Data Science at Airbnb and an Affiliated Researcher at Stanford University. In my past life I was a Research Fellow in Mathematics at Oxford University and then a High Frequency Trader on Wall Street.

My journey so far: I spent the first 28 years of my life living in the UK. I studied pure Mathematics at undergrad before becoming interested in statistical finance and completing a PhD in derivative pricing. At this point I became a big fan of all things Bayesian, especially methods for estimating unknown unobservable parameters of a system.

Then the 2008 Financial Crisis happened and the city was no longer interested in derivatives so after leaving academia I veered towards High Frequency Trading in New York. It was goodbye to stochastic calculus and hello to time-series analysis of enormous datasets.

I spent much of my time building models to predict movements in Foreign Exchange rates over the next few seconds, sometimes milliseconds. I would worry about the latency in live trading models and whether I could shave a few microseconds off a function call. It was a lot of fun and I worked with some of the smartest people I have ever met.

But I started to hear a lot of noise coming out of Silicon Valley. Every week some ‘tech startup’ would be ‘disrupting’ a market and raising another ‘series round’  of ‘hundreds of millions  of dollars’. The term ‘data scientist’ began to gather momentum and ‘big data’ was empowering new data-driven entrants into previously closed industries.

There is nothing new about the ‘data scientist’ role – its what has typically been referred to as a ‘quant’ in finance for decades. And there is nothing novel about ‘big data’ – its what financial markets have been churning out for dozens of years. But now other industries have caught up, which creates an opportunity to apply well understood techniques from finance to new problems in different datasets.

I couldn’t resist and moved to San Francisco, the heart of technology startups. Now I manage teams working on building Machine Learning models and Experimentation frameworks for user Growth and Retention. I have also collaborated with Academia to measure the interplay between Trust and the Sharing Economy.

Interested in: I love talking, writing, presenting topics in data science and comparing my experiences of academia to finance to tech. Please get in touch if you’d like to discuss any ideas more.