Andre Fernandes

I join MIDS with a professional data science background in financial services. My past experiences range from international product pricing, tree-based classifications and regressions, MCMC capital modeling, and deep learning. Currently, I am developing and deploying an NLP model using LSTMs to solve a complex classification problem where AI can assist human operators be more efficient in performing repetitive tasks. The deployment of this model features a wide range of applications: no-touch, low-touch, and human-guided implementation.

Next up in my pipeline is a Bayesian-Hierarchical model to tease out the individual human effect on data labeling where SME calibration is lacking. I'm excited to tackle this new project and add more Bayesian elements to my data science skillset.

On a more personal note, I live in Cambridge, MA and play competitive volleyball on my free time (though I don't have much!).