Fresh Grad Hire - Security Policy Engineer at moomoo

Hong Kong, Hong Kong Island, Hong Kong S.A.R. -

Full Time

Start Date

Immediate

Expiry Date

29 Jan, 26

Salary

0.0

Posted On

31 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Security Strategies, Fraud Risk Analysis, Data Mining, Graph Computing, Time-Series Mining, Machine Learning, Behavioral Anomaly Detection, Large Language Models, Risk Control, User Behavior Modeling, Countermeasures, AI Technology, Financial Security, Digital Assets, Web 3, Analytical Models

Industry

Financial Services

Description

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. 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. Open to candidates graduating between January 2025 and August 2026. Fluent in both English & Chinese. *Only shortlisted candidates will be contacted.

Responsibilities

Design security strategies for Digital Asset-related businesses and develop protective measures for account security and anti-fraud. Analyze fraud risks in Digital Asset/Web 3 scenarios and build models to monitor and counter specific user groups.