Principal Business Risk Control
About Us
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Responsible for supporting the fund security of various Line of Business products (such as wealth management, trading, RWA and other core products) to build real-time hierarchical risk control decision-making strategies based on equipment, behavior timing, transaction chain, relationship, and graph network characteristics.
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Risk Data Analysis, Capital Loss Quantification and Offense and Defense Review
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Based on Hive's massive transaction data, we use SQL and Python to conduct risk case mining and underground industry crime chain restoration. We continuously monitor core indicators such as real asset loss rate, block rate, accidental killing rate, positioning strategy vulnerabilities, and output special analysis reports.
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Strategy design, canary release experiment, iterative implementation
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Design rule strategy, responsible for policy canary release traffic allocation, AB experiment design, effect evaluation, promote strategy access to real-time decision engine online; continue to confront underground industry, form risk identification → disposal → review iteration closed loop.
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Emergency response to major asset losses: Participate in emergency hemostasis, risk tracing, and emergency blocking of major online fund safety accidents; precipitate underground industry intelligence and group characteristics, and build a risk feature database and intelligence database.
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Cross-team collaboration and risk control ability accumulation, linkage algorithm, product, R & D, compliance, anti-fraud operation team, integration of Machine Learning model, device fingerprint, behavior sequence ability optimization decision-making system; abstract general risk control ability, promote the construction of feature platform and risk Mid-Platform;
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Construction of risk index system, construction of scenario-based risk monitoring market, establishment of abnormal fluctuation warning mechanism, and promotion of long-term risk governance special project landing.
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Bachelor's degree or above, statistics, mathematics, computer science, financial engineering, data science preferred; Master's degree preferred.
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3-6 years of practical experience in payment/internet fund security and transaction anti-fraud risk control strategies, with experience in Alipay, WeChat Pay, top consumer finance, and bank online payment risk control preferred.
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Proficient in complex SQL (Hive/MaxCompute), proficient in Python for data mining and feature analysis; able to independently complete risk quantification and experimental evaluation.
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Deep understanding of payment risk scenarios: account takeover ATO, telecom fraud, fund benchmarking, abnormal batch transactions; familiar with real-time risk control chain, strategy Pushonline, indicator evaluation framework;
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Possess offensive and defensive thinking, able to actively perceive new underground industry means from massive data; good at finding the optimal balance point between capital loss, false interception, and business conversion.
Why Join Us
At Bybit, we are committed to fostering a supportive and enriching work environment.
Our benefits include:
- Study Growth Fund: We support your professional development and continuous learning.
- Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation.
- Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world.
- Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company.
- Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.
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