Senior Data Scientist

Description

About us Bitget is one of the world's leading digital assets ecosystems. With over 120 million registered users, Bitget has one of the most comprehensive suites of blockchain products and services available via bitget.com. Our mission is to support the growth of the digital assets industry and we believe it represents the future of finance. What we do empowers the future of finance by ensuring secure, efficient and smart digital transactions. We are one of the fastest growing companies in the digital asset sector. If you are looking for cutting-edge work, where you will have opportunities to develop your career among peers who are experts in their field, and you believe in the future of digital currency, then look no further than Bitget! What you'll do Responsible for the construction of risk control models in various risk domains, including but not limited to: Responsible for the construction of trading risk domain algorithms: constructing risk control models for trading behavior, covering multiple categories of trading scenarios such as spot, contract, and leverage. Real-time identification and warning of violations such as high-frequency trading, abnormal orders, market manipulation, spoofing, knock-on, and fake traffic. Responsible for the construction of risk domain algorithm models for financial products: constructing a user credit and risk scoring system, designing dynamic risk scoring models based on multidimensional behavioral data, asset data, and transa

Responsibilities

• Responsible for the construction of risk control models in various risk domains, including but not limited to:
• Push the risk control AI automation whole process to land quickly:
• Design and implement AI automated risk control process, integrate large language model (LLM), AI agent and graph algorithm, realize end-to-end automated closed loop of risk identification → rule generation → policy issuance;
• Build an AI Agent-driven risk control operation system to achieve automatic attribution of abnormal events, automatic generation of risk reports, and automatic recommendation of strategy optimization, greatly reducing manual intervention and improving the response speed and coverage breadth of risk control.
• Promote the construction of a model automation system, establish an automated pipeline for Model Training, Evaluation, Online, and Monitoring, and support rapid iteration and continuous optimization of models in multiple risk domains.
• Cross-team collaboration
• Work closely with product, strategy, data, compliance and other teams to deeply understand business needs and promote the efficient implementation of risk control algorithms.
• Establish risk control effect evaluation and review mechanism, continuously track model performance, and drive closed-loop optimization of strategies and algorithms.

Requirements

• Master's degree or above, majoring in computer science, statistics, mathematics, financial engineering, data science, etc., with a doctorate preferred;​
• AI Automation Capability: Familiar with LLM application development, Prompt Engineering, AI Agent framework, able to integrate AI capabilities into multi-domain risk control decision-making process; with MLOps experience, able to build model full lifecycle automation closed loop;​
• Business understanding ability: Have a deep understanding of risk control, anti-fraud, blockchain analysis and other businesses, and be able to design appropriate algorithm model solutions in combination with business scenarios;​
• Trading and financial product awareness: Have a certain understanding of the core business of cryptocurrency exchanges, including:​
• Trading business: Familiar with the operation mechanism of spot, contract, leverage and other trading categories, understand the basic concepts of order matching, liquidity management, market depth, etc., able to design targeted risk control models in combination with trading scenarios;​
• Exchange financial product business: Understand the business logic and risk characteristics of financial products such as wealth management, lending, pledge, structured products, etc., and be able to identify abnormal behavior and latent risks during the use of financial products.​
• Data Analysis Ability: High sensitivity to data, strong analytical and reasoning abilities, able to quickly locate key problems and drive optimization;​
• Collaboration ability: Strong cross-team communication and collaboration ability, able to promote the rapid closure of algorithm solutions on the business side.