Binance Accelerator Program - Data Scientist

Binance is a prominent player in the global blockchain industry, known for operating the largest cryptocurrency exchange globally. With a user base spanning 100+ countries and over 300 million users, Binance prioritizes security, transparency, speed, liquidity, and a diverse range of digital asset products. The platform's offerings include trading, finance, education, research, payment solutions, institutional services, Web3 features, and more. By harnessing the potential of digital assets and blockchain technology, Binance aims to establish an inclusive financial ecosystem that promotes financial freedom and enhances global financial accessibility.

About Binance Accelerator Program

The Binance Accelerator Program is a well-structured, limited-time initiative tailored to engage Early Career Talent in the rapidly evolving Web3 sector. Participants will gain immersive insights into Binance operations, offering a firsthand experience within the world's leading blockchain ecosystem. The program emphasizes networking and skills development to help participants expand their professional connections and acquire valuable abilities to boost their career growth.

Who Can Apply

This opportunity is open to current university students and recent graduates.

Responsibilities

• Implement and oversee AI evaluation processes throughout our systems to ensure consistent performance monitoring and enhance AI models continuously.
• Conduct thorough data analysis to detect patterns, anomalies, and areas for improving model effectiveness.
• Develop and maintain scalable data pipelines for processing raw data, performing transformations, and supporting downstream systems.
• Collaborate with diverse teams, including security, engineering, and product units, to integrate security and compliance principles into the software development lifecycle.
• Automate repetitive tasks and introduce solutions to streamline operational workflows.

Basic Requirements

• Proficiency in Python, including experience in utilizing libraries like requests for API calls and handling json data formats.
• Strong skills in data processing with PySpark and SQL (Hive) for managing large datasets in distributed environments.
• Solid grasp of software development fundamentals, with expertise in version control using Git.
• Demonstrated problem-solving prowess with a logical approach to analyzing challenges, root cause identification, and effective solution formulation.
• A keen willingness to learn, coupled with excellent communication abilities to interact productively with team members and proactively tackle assigned tasks from inception to completion.

Preferred Requirements

• Previous involvement in AI or evaluation-focused projects, showcasing familiarity with AI concepts, data labeling, model assessment, or related methodologies.
• Understanding of large language models (LLM) and associated issues to enhance model reliability and trustworthiness.
• Practical experience with tools like Label Studio for data annotation and Airflow for workflow orchestration.

Why Binance:

• Contribute to shaping the future within a leading blockchain ecosystem.
• Collaborate with top-tier professionals in a global, user-centric organization with a flat structure.
• Work on innovative, challenging projects in a fast-paced environment with autonomy and creativity.
• Thrive in a results-driven workplace with opportunities for career advancement and continuous learning.
• Competitive salary and comprehensive company benefits provided.
• Flexible work-from-home arrangements based on the nature of the business team's work.

Binance upholds equal employment opportunities, recognizing the significance of a diverse workforce in achieving organizational success. A confirmation of having read and agreeing to the Candidate Privacy Notice is required upon job application submission. The company employs artificial intelligence tools to support recruitment processes and enhance decision-making, with final hiring determinations made by humans. Contact us for more details on data processing practices.