Binance Accelerator Program - Data Scientist (AI Platform)

at  Binance

Binance is the global blockchain company behind the world’s largest digital asset exchange by trading volume and users, serving a greater mission to accelerate cryptocurrency adoption and increase the freedom of money.
Are you looking to be a part of the most influential company in the blockchain industry and contribute to the crypto-currency revolution that is changing the world?

REQUIREMENTS:

• Master’s or PhD in Data Science, Computer Science, Statistics, or a related field.
• Rich experience in AI and machine learning, with a strong emphasis on developing and applying Large Language Models (LLMs) such as GPT, BERT, T5, etc.
• Proficiency with common machine learning and deep learning frameworks such as TensorFlow, PyTorch, Scikit-Learn, etc.
• Strong programming skills in Python or other relevant languages for data analysis and modeling.
• Experience with handling and analyzing large-scale datasets, and familiarity with SQL and NoSQL databases.
• Practical experience with Q&A systems, natural language generation and understanding, image processing, and machine translation projects.
• Excellent problem-solving abilities and communication skills, with the ability to work efficiently in cross-functional teams.
• Up-to-date knowledge of the latest AI technology trends, with a strong capacity for learning and innovation.

• Design, develop, and optimize AI models and algorithms for Q&A systems, content generation and review, image generation and review, and translation projects.
• Collaborate with product managers, engineers, and other data scientists to understand business needs and translate them into technical solutions.
• Conduct experiments using data-driven approaches to evaluate and improve the performance of AI models.
• Develop and maintain high-quality datasets, ensuring data accuracy and completeness.
• Research and apply the latest AI technologies and tools to drive innovation and development within the company.
• Write clear technical documentation and reports, sharing research findings and technical experiences.