Fresh Grad Hire - Security Policy Engineer

About Us

As the "Guardians of Security" for Futu's financial ecosystem, we focus on leveraging technology to combat risks and safeguard trust. Join us, and you will:

• Lead or deeply participate in the end-to-end development of advanced financial anti-fraud algorithms, addressing the most complex security challenges in the financial sector.
• Build analytical models based on billion-scale data, engage in precise countermeasures against various sophisticated cybercriminal rings, and directly deliver tangible business security value.
• Take part in the practical implementation of Large Language Models (LLM) in security scenarios, exploring innovative applications of AI technology in risk identification and anomaly prevention.

If you aspire to achieve technological breakthroughs in the high-value field of financial security, we look forward to having you join forces with us.

Key Responsibilities

• Design security strategies for Digital Asset-related businesses, including the development and optimization of protective measures for account security, anti-fraud, and financial risk control.
• Identify and analyze fraud risks in Digital Asset/Web 3 scenarios (such as high-frequency abnormal transactions, fund pooling, fund theft), and summarize characteristics of malicious activities, profit models, and key behavioral chains.
• Build models based on user behavior data to monitor and counter specific user groups, combating black/gray industry chains.

Requirements

• Bachelor’s degree or higher in Computer Science, Information Security, Data Analysis, Statistics, or a related field.
• Understanding of behavioral anomaly detection techniques with the ability to identify and investigate fraudulent activities.
• Skilled in using data mining, graph computing, and time-series mining to construct multi-factor, multi-dimensional security profiles for users, devices, and environments, supporting risk control decision-making.
• Familiar with common machine learning algorithms (such as classification, regression, clustering, anomaly detection). Knowledge of prompt engineering and fine-tuning techniques in the field of large language models is a plus.
• Fluent in English and Chinese (both spoken and written).
• Open to candidates graduating between January 2025 and August 2026.

*Only shortlisted candidates will be contacted.