Senior Researcher, Natural Language Processing

1 Year ago • 3-5 Years
Data Analysis

Job Description

This role requires a skilled NLP researcher with expertise in Chinese word segmentation, part-of-speech tagging, sentence analysis, named entity recognition, text classification, and sentiment analysis. Deep learning experience with algorithms like RNN, CNN, LSTM, and GAN is preferred.
Good To Have:
  • Big Data Mining
  • Knowledge-Graph
  • Deep Learning
  • Sentiment Analysis
Must Have:
  • NLP Fundamentals
  • Statistical Models
  • Machine Learning
  • NLP Projects
Perks:
  • Game Development
  • Global Presence

Add these skills to join the top 1% applicants for this job

algorithms
deep-learning
text-classification
data-structures
sentiment-analysis
game-texts

Responsibilities:

About LightSpeed

Lightspeed Studios are one of the world’s most innovative and successful game developers. We are expanding across China, the United States, Singapore, Canada, Japan, South Korea, and New Zealand.

Founded in 2008, LightSpeed Studios has created over 50 games across multiple platforms and genres for more than 4 billion registered users. It is the co-developer of the worldwide hit PUBG MOBILE.

Responsible for NLP research and development including Chinese word segmentation, part-of-speech tagging, sentence analysis, and named entity recognition.

Responsible for text classification, sentiment analysis, data mining, text generation, topic analysis, label extraction, and other research and development job.

Optimize existing online algorithms, develop efficient and reliable NLP solutions by combining business needs and data.

Explore applications of NLP techniques and deep learning algorithms in games.

Follow the latest developments in academia and industry and quickly apply findings in your work.

Requirements:

Familiar with NLP fundamentals, with a strong understanding of statistical models, related machine learning principles, and experience working on NLP related projects.

Proficient in at least one programming language, familiar with basic data structures and algorithms.

Experience in big data mining, knowledge-graph auto-making, and deep learning experience is preferred.

Familiar with word segmentation, part-of-speech tagging, entity recognition, sentence analysis, model pre-training. Experience in sentiment analysis, relationship extraction, and event extraction is preferred.

Publication of academic results in academic journals and conferences in NLP-related fields (such as: EMNLP, ACL) is preferred.

Familiar with CRF, SVM, and other classic machine learning algorithms and tools, word vectors, RNN, CNN, LSTM, GAN, and other deep learning experiences are preferred.

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