Binance

Data Scientist (Search & Recommendation)

Binance Hong Kong Island, Hong Kong, China

Technology, Information and Internet · 5,001-10,000 employees

4 d ago
Remote data-scientist Senior (5-10 yrs) Full-time China
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About the role

Design and manage search and recommendation services and models, developing core content recommendation modules to improve content matching, distribution, user experience, and business outcomes. Collaborate with content, business, and product teams to identify opportunities and define success metrics.

What they look for

Recommendation Systems Search Recommendation Machine Learning Personalization Content Matching Content Distribution Data-Driven Strategy PyTorch TensorFlow Large-Scale Application Development Cross-Team Collaboration Success Metrics

Requirements

Requires an MSc or PhD in a relevant field and at least five years of relevant industry experience; content-domain experience is preferred. Candidates should have hands-on experience with PyTorch or TensorFlow, large-scale user-facing application development, and strong cross-team collaboration skills; top-tier publications are a plus.

Benefits

Competitive Salary Company Benefits Career Growth Opportunities Continuous Learning

Full description

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, and more. Our mission is to increase the freedom of money and financial access for people around the world.

Responsibilities

  • Design and manage search recommendation services and models to support the content team, empowering content ecosystem development.
  • Utilize machine learning-based personalization methods, design patterns, and tools to enhance content matching and distribution efficiency.
  • Deep understanding of recommendation systems within the content domain, leveraging business knowledge to drive AI product upgrades and improve content experience and business outcomes.
  • Lead the development of core content recommendation modules using data-driven strategies to maximize content value and user impact.
  • Collaborate with content, business, and product management teams to identify needs and opportunities within content scenarios, and jointly define success metrics.

Requirements

  • MSc or PhD in Machine Learning, Computer Vision, Computer Science, or Applied Mathematics, with at least 5 years of relevant industry experience (experience in the content domain is preferred).
  • Strong hands-on experience with popular machine learning frameworks such as PyTorch or TensorFlow.
  • Experience in large-scale application development, preferably in content-related user-facing applications.
  • Excellent cross-team collaboration skills with the ability to work effectively with global content teams.
  • Publication record at top-tier conferences or journals is a plus.

Why Binance

  • Shape the future of finance
  • Collaborate with world-class talent in a user-centric global organization with a flat structure
  • Tackle challenging projects in a fast-paced and innovative enviornment with autonomy
  • Thrive in a results-driven workplace with opportunities for career growth and continuous learning
  • Competitive salary and company benefits
  • Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.

By submitting a job application, you acknowledge that you have read our Candidate Privacy Notice.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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