Data Scientist (Recommendation Systems), Binance Square job opportunity at Binance.

Home Jobs In Taiwan Tag: Personalization Data Scientist (Recommendation Systems), Binance Square position at Binance


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Binance Data Scientist (Recommendation Systems), Binance Square
Experience: 3-years
Pattern: full-time
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Personalization

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degreeBachelor's (B.Sc.)
loacation Taipei, Taiwan
loacation Taipei....Taiwan

Design, develop, and manage recommendation services and models to power personalised user experiences. Apply machine learning–driven 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. __ Requirements: Bachelor’s or Master’s 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 learning–driven 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. Preferred Qualifications: 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.

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