Research Fellow, Department of Analytics and Operations

Updated: 7 days ago
Job Type: FullTime
Deadline: 09 Feb 2022

Job Description

We are looking for an experienced data scientist to join us at NUS Business Analytics Labs to develop data intensive high-performance applications. You should be comfortable with cloud services such as AWS, Google Cloud. Container orchestration will be plus.

  • Responsible for the research and development and iteration of scenario recommendation algorithm, including retrieval, coarse ranking, precise ranking, and re-ranking, etc., to improve user experience and revenue
  • Implement federated recommender systems to preserve privacy with differential privacy and other data privacy-preserving methods
  • Analyze business data and formulate corresponding recommendation strategies
  • Communicate with relevant business teams and participate in the assessment and implementation of business needs.
  • Create MLFlow pipelines to deploy, monitor and conduct user experiments using larger deep learning models

Job Requirements

  • A PhD in Computer Science, Information Systems, Data Science or Operations Research
  • Solid algorithmic skills and excellent coding ability in Python, PyTorch/tensorflow framework and SQL
  • Familiar with various retrieval algorithms, Click-through Rate/Conversion Rate estimation, re-ranking models, etc.
  • Able to understand the business in depth, grasps concepts easily and is sensitive to data.
  • At least 3 years of algorithm development experience in recommendation, search, and advertising, working experience in e-commerce is preferred
  • Strong organizational and management skills.
  • Goal-oriented, proactive, and able to execute projects effectively good communication skills and teamwork spirit
  • Familiarity with NLP is preferred. Should be comfortable using machine learning and deep learning approaches to recommender systems and NLP.

More Information

Location: Kent Ridge Campus
Organization: School of Business
Department : Analytics And Operations
Employee Referral Eligible: No
Job requisition ID : 9074


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