Data Scientist
CurrentDeveloped Bayesian inference models for demand forecasting. Implemented improvements in models such as leveraging text mining techniques to generate additional features, adding business logic to address customer feedback, and utilizing data structures that allow for more efficient computations. Have employed techniques with hash tables, parallel computing, and sparse data structures in order to efficiently preprocess collected data. Leveraged features of the Julia programming language in order to build a complex inventory optimization model that could run tens of thousands of optimizations on millions of rows of collected data in an efficient and general way and was able to demonstrate more than 10x improvement in processing time over other implementations.
