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Machine Learning Engineer - Global Payment - Singapore

面议
新加坡 · Singapore(新加坡) · 经验要求见详情
研发机器学习正式L6742新加坡国际招聘

关于这个机会

About the team The Global Payment team of Bytedance provides payment solutions - including payment acquisitions, disbursements, transaction monitoring, payment method management, foreign exchange conversion, accounting, reconciliations, and so on to ensure that our users have a smooth and secure payment experience on ByteDance platforms including TikTok. Global Payments Data Intelligence team's works to minimise the frequency and damage of inauthentic behaviours in supporting international businesses (TikTok Live, TikTok Shop, etc) with a data-driven approach. For example, this team is focused on optimising key payment metrics including but not limited to: fraud rate, chargeback rate, compliance rate, etc, through data intelligence approach to provide quality values to our customers. Responsibilities 1. Build Machine Learning models to respond to and mitigate risks in Global Payments products; 2. Improve modelling infrastructures, labels, features and algorithms towards improving robustness, automation and generalisation, as well as, reduce modelling and operational load on risk adversaries and new product/risk ramping-ups; 3. Level up the risk Machine Learning expertise excellence in domain areas such as privacy/compliance, interoperability, risk perception, analysis, etc;

任职要求

Minimum Qualifications: - Bachelor degree or above in Computer Science, Statistics, Mathematics or other related majors; - Proficient in Python, Java or Scala and big data tools such as SQL / Hive / Spark, etc; - Domain experiences in one of these fields is preferred: trust and safety, risk management, fraud, anti-fraud, etc. - Experienced in Machine Learning and Deep Learning models; Preferred Qualification: - 5 years and above of Machine Learning experience, preferably with domain experiences in Trust & Safety, Risk management, Anti Fraud;

官方来源与核验

字节跳动官方招聘 · 职位编号 7176130204065433914

最近核验:2026-09-16T14:05:07.210038+00:00

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