Data Scientist

: Data Scientist (Recommendation Systems)

Location: Asia / Australia, Brisbane / Australia, Melbourne / Australia, Sydney / Hong Kong / New Zealand, Auckland / New Zealand, Wellington / Taiwan, Taipei
Department: Engineering Data Science/AI
Employment Type: Full-time: Remote

Binance is a leading global blockchain ecosystem behind the worlds largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 280 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, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

As a Data Scientist for Binance Square, you will be responsible for designing and managing recommendation services and models that power personalised user experiences on our social content platform. You will apply advanced Machine Learning personalisation techniques, leveraging design patterns and tools to deliver highly relevant and engaging content to users.

With a strong foundation in recommendation systems and an understanding of the Web3 and crypto business domain, you will drive the development of core modules using data-driven strategies to maximise impact. You will also play a key role in identifying user needs and growth opportunities, collaborating with Business and Product teams to define success metrics and measure the value of AI-driven personalisation.

This role requires both technical depth and product intuition to elevate the impact of Binance Square as the go-to platform for the global crypto community.

• Design, develop, and manage Recommendation services and models to power personalised user experiences.
• Apply Machine Learningdriven personalisation methods, design patterns, and tools to deliver scalable solutions.
• Leverage deep expertise in Recommendation systems combined with business domain knowledge to elevate the impact of AI products.
• Drive the development of core modules using data-driven strategies to maximise business and user value.
• Partner with Business and Product teams to identify opportunities, define success metrics, and ensure measurable impact.

• Bachelors or Masters degree in Machine Learning, Computer Vision, Computer Science, Applied Mathematics, or a related field, with at least 3 years of relevant industry experience.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Proven experience designing, developing, and managing large-scale recommendation systems for personalised user experiences.
• Strong expertise in machine learningdriven personalisation methods, algorithms, and frameworks.
• Demonstrated ability to build scalable, production-grade solutions applying modern software engineering practices.
• Solid understanding of data-driven product development, with experience developing and optimising core modules to maximise business and user value.
• Strong collaboration skills, with experience partnering across Business, Product, and Engineering teams to define opportunities, establish success metrics, and ensure measurable outcomes.

• Deep knowledge of Recommendation Algorithms (e.g., collaborative filtering, content-based, sequence models, graph-based methods, reinforcement learning).
• Experience with experimentation platforms (A/B testing, multi-armed bandits) and defining product success through data-driven experimentation.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and ML/AI infrastructure.
• Strong business acumen and the ability to translate business needs into effective AI-driven solutions.
• Track record of publishing or contributing to research in the field of recommender systems or personalisation.

• Shape the future with the worlds leading blockchain ecosystem.
• Collaborate with world-class talent in a user-centric global organization with a flat structure.
• Tackle unique, fast-paced projects with autonomy in an innovative environment.
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning.
• Competitive salary and company benefits.
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team).

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

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