- Company Name
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- Job Title
- Machine Learning Engineer, Global Payment Decision Science - USDS
- Job Description
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Job title: Machine Learning Engineer, Global Payment Decision Science – USDS
Role Summary: Design, develop, and deploy machine‑learning models for payment services, focusing on fraud prevention, AML, user experience optimization, and campaign management. Own the full model lifecycle, from problem translation and feature engineering to deployment and monitoring, ensuring robustness, automation, and compliance.
Expectations: Deliver measurable business impact through high‑quality ML solutions; collaborate closely with product, risk, and compliance stakeholders; continuously improve model infrastructure, labeling, and feature pipelines; adhere to data privacy and security standards; stay current on cutting‑edge AI technologies such as deep learning and large‑language models.
Key Responsibilities:
- Translate payment business challenges into data‑science and algorithmic solutions.
- Build and refine models using ML and deep‑learning techniques for fraud, AML, risk scoring, and personalization.
- Own end‑to‑end model lifecycle: data preparation, feature engineering, training, validation, deployment, and monitoring.
- Enhance modeling infrastructure, labeling workflows, feature stores, and algorithm performance for scalability and generalization.
- Apply advanced AI (e.g., DNN, LLM) to payment‑related datasets.
- Ensure models meet privacy, compliance, and interoperability requirements.
Required Skills:
- 3+ years of applied machine‑learning experience, preferably in risk management or trust & safety.
- Proficiency in big‑data processing (SQL, Hive, Spark).
- Mastery of at least one data‑science programming language (Python, Java, or Scala).
- Strong background in ML and deep‑learning algorithms.
- Excellent problem‑solving and communication skills.
Required Education & Certifications:
- Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, or related field.
- (No specific certifications required, but experience in fintech or payment compliance is a plus.)