DataVisor

Senior Data Scientist – Fraud Detection

DataVisor

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇯🇵 Japan

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Job Level

Senior

Tech Stack

AWSAzureCloudCyber SecurityGoogle Cloud PlatformHadoopPySparkPythonSparkSQL

About the role

  • Lead the full lifecycle of fraud detection features and models, from ideation and data exploration to prototyping, productionizing, and monitoring.
  • Develop highly predictive features from complex, large-scale, multi-dimensional data, including user behavior, device intelligence, network graphs, and transaction records.
  • Research, design, and implement state-of-the-art machine learning algorithms, combining supervised, unsupervised, and semi-supervised techniques to detect novel and evolving fraud patterns.
  • Work with massive, noisy, and imbalanced datasets (billions of events) using tools like Spark, SQL, and our proprietary AI platform.
  • Partner closely with Engineering to ensure robust, low-latency model deployment and with Product Management to translate complex client needs into technical solutions.
  • Conduct deep-dive analyses on fraud attacks, extract actionable insights, and translate them into improved detection strategies and rules.
  • Provide technical guidance and mentorship to junior data scientists, fostering a culture of excellence and continuous learning.

Requirements

  • Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • 5+ years of professional experience in data science, with a significant focus on fraud detection, cybersecurity, or a related adversarial domain.
  • Deep, hands-on experience with machine learning lifecycle in a production environment.
  • Strong programming skills in Python (must-have) and proficiency with SQL. Experience with PySpark is a significant plus.
  • Solid understanding of both classic machine learning models (Logistic Regression, Gradient Boosting, etc.) and modern techniques (Deep Learning, Graph Neural Networks).
  • Proven experience with feature engineering and a keen intuition for what makes a feature predictive and robust in a dynamic environment.
  • Experience with large-scale data tools (Spark, Hadoop, etc.) and cloud platforms (AWS, GCP, Azure).
  • Professional proficiency in written and spoken English, with the ability to collaborate effectively in a global, cross-functional team.
  • Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
  • Based in Japan
Benefits
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Applicant Tracking System Keywords

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Hard skills
machine learningfraud detectiondata explorationfeature engineeringPythonSQLPySparkLogistic RegressionGradient BoostingDeep Learning
Soft skills
technical guidancementorshipcollaborationcommunicationanalytical thinkingproblem-solvingadaptabilityinsight extractionteamworkcontinuous learning
Certifications
Master's degreePhDComputer ScienceStatisticsMathematics