• 3+ years’ full-time work experience with a Master's degree in one of the following fields:: Machine Learning, Engineering, Applied Mathematics, Applied Physics, Computer Science, Statistics, Economics, or Quantitative Finance.
• Comfortable using computer programming languages and data warehousing tools to define and build statistical models for identification, estimation, and prediction.
o Practical experience in SQL on RDBMS or NoSQL environment
o Working knowledge of at least one modeling framework such as Python (numpy,
pandas, scikit-learn, TensorFlow, Pytorch, etc.), R (Tidyverse and common
statistical packages), Matlab, etc.
o Experienced in manipulate large data set and exploratory data analysis with data visualization technology such as Tableau, ggplot and D3.js.
• Proficient in discrete multivariate stochastic process, statistical inference and analysis.
• Can translate user requirements into a functional model and interpret predictive models to non-technical stakeholders
• Experience using a data-driven approach in at least one of the following fields: marketing, sales, media, gaming, studio production, or user experience.
• (Plus)Practical experience in building production level deep learning models using AI framework such using one or more including but not limiting to the following edge inference open source projects. i.e. TensorFlow, Caffe/2, Mxnet, and Android NNAPI.
• (Plus) Practical experience in measurement of offline advertising, geospatial analytics, or retail network optimization