Description:

Binance is seeking a Lead Data Scientist for their Recommendation team, based in Asia, with a remote work option.
The company is a leading global blockchain ecosystem and cryptocurrency infrastructure provider, aiming to accelerate cryptocurrency adoption.
The role involves leveraging rich data and state-of-the-art machine learning infrastructure to develop data products for millions of cryptocurrency users.
Responsibilities include designing and managing search recommendation services and models, utilizing machine learning-powered personalization methods, and driving the development of core modules with a data-driven strategy.
The candidate will collaborate with engineers, data analysts, and product/marketing managers to define and build solutions based on rich data and cutting-edge technology.
The position offers an opportunity to enhance machine learning and data science skills while making a significant impact on blockchain and cryptocurrency technology.

Requirements:

A Master's or PhD in Machine Learning, Computer Vision, Computer Science, or Applied Mathematics is required, along with at least 5 years of relevant industry experience.
Candidates must have excellent hands-on experience with popular machine learning frameworks such as PyTorch or TensorFlow.
Bilingual proficiency in English and Mandarin is required for effective coordination with stakeholders.
Experience in leading a team and application development practices at scale is essential.
Good global team collaboration skills and experiences are advantageous.
A publication record at top conferences and journals is considered a plus.

Employees will be part of a leading blockchain ecosystem that offers excellent career development opportunities.
The work environment is diverse, with world-class talent and endless learning and growth opportunities.
Employees will tackle fast-paced, challenging, and unique projects in a truly global organization with a flat organizational structure.
Competitive salary and benefits are provided.
Flexible working hours, a remote-first approach, and casual work attire are part of the company culture.