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Staff Data Scientist, Identity

Riskified·Tel Aviv, Израиль·en
ГибридПолная занятостьData ScienceEnterprise SoftwareeCommerce

Drive the research and development of machine learning models for identity resolution and fraud prevention, from initial research through integration into high-throughput production systems.

Обязанности

  • Set the research roadmap and technical standards for identity resolution
  • Architect and advance an identity graph engine using graph models, transformers, and other machine learning methods
  • Build scalable predictive and representation-learning models for large tabular, sequence, and graph datasets
  • Guide research projects from concept through production deployment
  • Integrate machine learning pipelines into real-time production environments with data engineering, software, and product teams
  • Evaluate current academic research and apply relevant methods to practical problems
  • Mentor senior data scientists

Требования

  • MSc or PhD in computer science, statistics, mathematics, or a related quantitative field
  • At least 6 years of experience designing, training, and deploying complex machine learning models in large-scale production environments
  • Expertise in transformers, deep neural networks, graph neural networks, or advanced tabular learning
  • Practical experience with distributed data processing systems such as Spark or Databricks, and with graph databases or frameworks
  • Technical leadership experience, including setting architectural direction and translating business requirements into algorithmic solutions

Будет плюсом

  • Experience in fraud detection, risk management, or fintech
  • Experience in identity resolution, entity disambiguation, link analysis, or complex network modeling

Условия и преимущества

  • Equity for all employees
  • Pension and Keren Hishtalmut
  • Private medical insurance
  • Additional time off for parents and caregivers
  • Commuter and parking benefits
  • Team events, meals, and fitness activities
  • Volunteer opportunities and professional development programs

Соответствие

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