Job Summary: Responsibilities: Frame the business problem and model if it can be resolved by machines' solutions Improve actionable insights from data/models through applying various algorithmic techniques Select the right analytic techniques and set of potential algorithms to resolve complex business questions Develop mathematical models using Linear Algebra, Statistics and Probability or Geometry at an optimize level Develop company A/B testing framework and test model/solution quality on various machines on Cloud. Collaborate with Data Scientist team to identify data requirement, model improvement, as an input to the distributed solution process Perform the series of experiments with data and multiple algorithms Convert statistical results into consumable information for business usage Identify the solution to deploy the analytic product into the business operation process Provide Operations and Production support to operationalized (deployed) models Evaluate the modeling results and identify improvements after production as a full AI lifecycle Qualifications: Bachelor's degree or higher in Engineering and Science fields Experience in the AI/Data science lifecycle including data understanding, modeling, and deployment at least 5 years Strong skill in coding and computation using Python (must) and others Experience in Big Data and Cloud computing Experience in either open-source or proprietary software "Make it done" Attitude and open to learn new things Quantitative and Growth Mindsets Excellence in communication and data storytelling Experience with machine learning algorithms and statistics including regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, and so on. Qualified AI portfolio Good command of spoken & written English (Minimum TOEIC Score 500)