Binance Accelerator Program - Data Scientist (Recommendation/Square Community)
๐ฎ๐ณ India | ๐ธ๐ฌ Singapore | ๐ฏ๐ต Japan | ๐น๐ญ Thailand | ๐จ๐ณ China | ๐ฎ๐ฉ Indonesia | ๐ง๐ฉ Bangladesh | ๐ฎ๐ท Iran | ๐ฏ๐ด Jordan | ๐ฐ๐ฟ Kazakhstan | ๐ฒ๐พ Malaysia | ๐ณ๐ต Nepal | ๐ต๐ฐ Pakistan | ๐ต๐ญ Philippines | ๐ฐ๐ท South Korea | ๐ฑ๐ฐ Sri Lanka | ๐น๐ผ Taiwan | ๐น๐ท Turkey | ๐ป๐ณ Vietnam | ๐ฑ๐ง Lebanon | ๐ฒ๐ฒ Myanmar | ๐ฑ๐ฆ Laos | ๐พ๐ช Yemen | ๐ฒ๐ป Maldives | ๐ด๐ฒ Oman
Python
Finance
Machine Learning
Design
Blockchain
Data Science
SQL
Testing
Binance Accelerator Program - Data Scientist (Recommendation/Square Community)
from ๐ฎ๐ณ India | ๐ธ๐ฌ Singapore | ๐ฏ๐ต Japan | ๐น๐ญ Thailand | ๐จ๐ณ China | ๐ฎ๐ฉ Indonesia | ๐ง๐ฉ Bangladesh | ๐ฎ๐ท Iran | ๐ฏ๐ด Jordan | ๐ฐ๐ฟ Kazakhstan | ๐ฒ๐พ Malaysia | ๐ณ๐ต Nepal | ๐ต๐ฐ Pakistan | ๐ต๐ญ Philippines | ๐ฐ๐ท South Korea | ๐ฑ๐ฐ Sri Lanka | ๐น๐ผ Taiwan | ๐น๐ท Turkey | ๐ป๐ณ Vietnam | ๐ฑ๐ง Lebanon | ๐ฒ๐ฒ Myanmar | ๐ฑ๐ฆ Laos | ๐พ๐ช Yemen | ๐ฒ๐ป Maldives | ๐ด๐ฒ Oman
About the Role
We are looking for a Data Scientist early careers talent to join the Binance Square team and support the development of next-generation recommendation and community intelligence systems.
Binance Square is evolving from a content feed into an intelligent Web3 financial community, helping users discover market trends, trading ideas, hot topics, and high-quality creators. In this role, you will work closely with data scientists, algorithm engineers, product managers, and business teams to improve content distribution, user engagement, and community growth through data-driven recommendation strategies.
Responsibilities
Support the optimization of key recommendation scenarios, including Feed, Hot Tab, Topic, News, Trading Analysis, and creator distribution.
Build and refine data metrics for content quality, user interest profiling, creator quality, community health, and trading-related content.
Participate in recommendation strategy design, including recall, ranking, cold-start, diversity, personalization, and traffic allocation.
Conduct A/B testing, metric monitoring, bad-case analysis, and experiment deep dives to evaluate algorithm and product impact.
Explore the application of LLMs and multimodal models in content understanding, topic tagging, hot event detection, and personalized distribution.
Work with engineering teams to improve data pipelines, feature logging, experiment tracking, and recommendation system efficiency.
Requirements
Strong analytical skills and solid understanding of statistics, machine learning, and data mining.
Proficient in SQL and at least one programming language such as Python.
Familiar with recommendation systems, ranking models, user profiling, A/B testing, or causal analysis.
Good business sense and ability to translate data insights into product or algorithm improvements.
Strong communication skills and ability to work cross-functionally with product, algorithm, engineering, and operations teams.
Interest in Web3, crypto, financial markets, online communities, or content recommendation is a plus.






