Infocast is looking for a data scientist to help create and expand functionalities for our upcoming and existing products. The ideal candidate should have a solid understanding (both theoretical and practical) of machine learning techniques, Deep Learning and NLP technologies, with the ability to deploy them on a large scale. In this role, you are expected to be highly analytical and possess critical thinking skills.

• Partner up with project managers and technical team to assist in deciphering business requirements to technical solutions
• Coordinate with front-end and back-end developers to set up machine learning pipelines
• Build reusable functions and libraries to pre-train models for existing and future projects
• Track dataflows and system processes by incorporating them in testing, staging, and production environments
• Ability to plan and explain machine learning models before development commences
• Develop and deploy both traditional statistical models and machine learning techniques and algorithms: Regression, clustering, neural networks, Anomaly Detection, Random Forests etc. to improve prediction and forecasts of desired metrics.

• Ability to communicate clearly in Mandarin and English both verbal and written
• Strong understanding in software development techniques, both procedural and non-procedural language
• Strong proficiency in Python and Java
• Experienced in using machine learning libraries (including Pandas, Numpy, Scikit-learn, XGboost, etc.)
• Experienced in using deep learning frameworks (Tensorflow, Pytorch, Keras)
• Familiar with the machine learning models (Decision tree, Random Forests, Gradient Boosting, Linear regression, Support Vector Machine (SVM), Multiple Layer Perceptron (MLP), etc.)
• Familiar with Natural Language Processing (NLP) subjects (Stop Words, TF-IDF, Sentence Segmentation, Lemmatization, etc.), and Computer Vision (CV) subjects (Object detection, Image Classification)
• Familiar with the advanced math (such as Multivariable Calculus, Linear Algebra) and Statistics (hypothesis testing, probability distribution)
• Familiar with Deep learning subjects (Convolutional Neural Network (CNN), Recurrent Neural Network(RNN))