Alex is currently a Data Scientist Analyst at Remitly. He has expertise in Python, Spark, and Deep Learning.
Python is the glue that makes his day-to-day work as a data scientist sing. Alex uses Python primarily for data mining and data science, but also for data engineering tasks, especially ETL.
Alex has used Apache Spark extensively for data science projects, particularly making use of MLLib for doing supervised and unsupervised learning on large, sparse data formats stored in HDFS. Alex tends to use both the Scala and Python APIs, depending on how fast he wants to iterate and also where the current functionality is exposed.
Alex has given public talks about doing Deep Learning using Python. He is familiar with several Python-related deep learning interfaces, including, but not limited to, caffe, Theano, Torch, Graphlab-Create, Nervana Sys, etc. Additionally, he is studying the theoretical properties of different kinds of neural networks and am applying this knowledge to analyze interesting data sets and solve interesting data problems, such as computer vision and transfer learning.
Outside of work, he loves Kaggle competitions, is diving deep into tensor libraries, and is exploring machine learning on GPUs. Alex is a graduate of the University of Chicago with degrees in Mathematics and Economics.