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DataVisorDA

Senior Data Scientist - Fraud Detection

DataVisor is an AI-powered fraud and risk management platform that utilizes unsupervised machine learning to help enterprises detect and prevent various digital threats in real-time.

DataVisor

Employee count: 51-200

Japan only

About DataVisor:

DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.

Key Responsibilities:

  • End-to-End Model Development: Lead the full lifecycle of fraud detection features and models, from ideation and data exploration to prototyping, productionizing, and monitoring.
  • Advanced Feature Engineering: Develop highly predictive features from complex, large-scale, multi-dimensional data, including user behavior, device intelligence, network graphs, and transaction records.
  • Algorithm Innovation: 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.
  • Large-Scale Data Processing: Work with massive, noisy, and imbalanced datasets (billions of events) using tools like Spark, SQL, and our proprietary AI platform.
  • Cross-Functional Collaboration: Partner closely with Engineering to ensure robust, low-latency model deployment and with Product Management to translate complex client needs into technical solutions.
  • Fraud Strategy & Analysis: Conduct deep-dive analyses on fraud attacks, extract actionable insights, and translate them into improved detection strategies and rules.
  • Mentorship: 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

PTO

About the job

Apply before

Posted on

Job type

Full Time

Experience level

Senior

Location requirements

Hiring timezones

Japan +/- 0 hours

About DataVisor

Learn more about DataVisor and their company culture.

View company profile

DataVisor is a global leader in AI-powered fraud and risk management. Founded in 2013, the company provides an end-to-end Software-as-a-Service (SaaS) platform that leverages advanced artificial intelligence and machine learning capabilities to protect large consumer-facing enterprises and financial institutions from a wide array of digital threats. These threats include fraudulent transactions, spam, fake reviews, promotion abuse, fake application installs, identity theft, and money laundering. DataVisor's mission is to build and restore trust online by enabling organizations to proactively combat evolving fraud patterns in real-time.

The company's platform is distinguished by its patented unsupervised machine learning (UML) technology. This approach allows the system to identify new and unknown malicious actors and coordinated fraud rings without relying on historical labels or training data, which is crucial for staying ahead of sophisticated and rapidly changing attack vectors. DataVisor's solutions are designed to be data-agnostic, capable of ingesting and analyzing vast amounts of data from various sources to provide a holistic view of risk. The platform offers comprehensive capabilities including data orchestration, real-time feature computation, a flexible decision engine, and powerful case management tools. It is built to scale, handling high transaction volumes with low latency, making it suitable for some of the world's largest organizations. DataVisor serves a diverse range of industries, including financial services, banking, credit unions, fintech, e-commerce, social platforms, and digital payments, helping them to reduce fraud losses, improve operational efficiency, minimize customer friction, and ensure regulatory compliance.

Claim this profileDataVisor logoDA

DataVisor

Company size

51-200 employees

Founded in

2013

Chief executive officer

Yinglian Xie, Fang Yu

Employees live in

View company profile

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