Binance Accelerator Program - Data Scientist (Recommendation/Square Community)

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.

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

Analyze user behavior, content quality, creator performance, and feed consumption patterns to identify opportunities for recommendation improvement. 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

Currently pursuing a Bachelor’s, Master’s, or PhD degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field. 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.

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.