Position: Applied Scientist
This position has full participants or has passed application deadline.
Location: Work Remotely
Company: A top IT company
Listed by QiShiCPC
Job description: We develop and implement large-scale machine learning solutions to protect the buying experience while minimizing friction for our selling partners. We develop state-of-the-art models (graph models, NLP, CV) to detect negative customer experience in real-time and build an ever-evolving risk monitoring system to proactively protect customer trust. In this role, you will work closely with scientists, economists and engineers to build end-to-end ML solutions that have immediate impacts on customers. You will work on a variety of research areas including: 1. Develop Graph/NLP/CV deep learning models to extract insights from customer feedback; 2. Build the next generation of risk monitoring system using predictive modeling, graph mining and unsupervised learning techniques; 3. Apply the state-of-the art Graph modeling/NLP/Computer Vision technique to develop a highly scalable ML solution for product authentication; 4. Develop and deploy real-time ML models.
Requirement: Requirement: 1. Master's degree in Computer Science, Statistics, Applied Math, Operations Research, Economics, or a related quantitative field; 2. Hands-on experience in developing machine learning models using Python, R, Java or other programming languages; 3. Ability to self-direct, multitask, and prioritize a constantly evolving workload. Preferred: 1. PhD in Computer Science, Statistics, Applied Math, Operations Research, Economics, or a related quantitative field; 2. Good knowledge and practical experience in statistics, machine learning, or deep learning; 3. Experience applying theoretical models in an applied environment; 4. Excellent oral and written communication skills including the ability to communicate effectively with both technical and non-technical stakeholders.
Announce date: March 18, 2021
Application deadline: April 18, 2021
Expire date: May 18, 2021
Premium or wild Card Members only
This position is free to apply
Maximum applicants: 100
2 people already applied
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