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Senior Data Scientist, Fraud
Senior Data Scientist, FraudWorld • San Francisco, CA, United States
Senior Data Scientist, Fraud

Senior Data Scientist, Fraud

World • San Francisco, CA, United States
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Senior Data Scientist, Fraud

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About The Company

World is a network of real humans built on privacy-preserving proof-of-human technology and powered by a globally inclusive financial network that enables the free flow of digital assets for all. It is built to connect, empower, and be owned by everyone.

About The Team

The Fraud and Risk Analytics team is responsible for detecting and preventing fraudulent activities that may endanger the health of the World ecosystem. Our unique growth model of using a global network of Orb Operators to give a free share of Worldcoin to everyone on Earth leads to numerous challenges that no company has ever encountered before. Potential fraud types include large-scale incentive fraud, social engineering fraud, and presentation attacks. Therefore, sophisticated fraud and risk analytics is essential for World’s long-term success.

About The Opportunity

We are looking to hire a Senior Data Scientist to work on the front lines of fighting fraud. You will be responsible for (a) investigating fraud alerts and incidents, (b) monitoring our fraud platform for anomalous activity and taking decisive action, (c) developing novel detection solutions using analytics and machine learning.

Responsibilities

  • Understand our products, systems and tools; investigate behavioral patterns through data analysis using SQL and other data scripting and visualization tools
  • Lead root cause analysis to identify opportunities to predict, prevent, and mitigate fraud risk according to business expectations
  • Investigate individual events using internal policies and review methodologies to determine if the transactions / events are fraudulent or not
  • Research fraud and user behavior to contribute to machine learning models, rules and other detection systems
  • Triage and forensically investigate fraud related escalations from internal and external stakeholders

Qualifications

  • Bachelor’s degree in a quantitative field; Master’s degree a plus
  • 6+ years of hands‑on experience as a Data Scientist
  • Extensive experience with SQL
  • Programming experience in at least one high‑level programming language (e.g., Python)
  • Experienced in analyzing data and comfortable making impactful decisions in a fast‑paced and sometimes ambiguous environment
  • Attention to detail and ability to multitask
  • Excellent problem‑solving and analytical skills
  • Strong business judgment and communication skills
  • Availability during periods of heightened risk (including on weekends and holidays)
  • Work experience in fraud analytics, fintech, payments, lending, banking, or financial institutions is a plus
  • Experience with building machine learning models a plus
  • High curiosity, strong autonomy, and a deep sense of ownership
  • Practically oriented and “getting‑the‑job‑done” mindset
  • Pay Transparency Statement (for CA and NY Based Roles)

    The reasonably estimated salary for this role at TFH in our San Francisco office ranges from $182,000 – $215,000 , plus a competitive long‑term incentive package. Actual compensation is based on factors such as the candidate’s skills, qualifications, and experience. In addition, TFH offers a wide range of best‑in‑class, comprehensive and inclusive employee benefits for this role including healthcare, dental, vision, 401(k) plan and match, life insurance, flexible time off, commuter benefits, professional development stipend and much more!

    The reasonably estimated salary for this role at TFH in our Munich office ranges from €125,000 – €155,000 , plus a competitive long‑term incentive package, and may include variable compensation. Actual compensation is based on factors such as the candidate’s skills, qualifications, and experience.

    By submitting your application, you consent to the processing and internal sharing of your CV within the company, in compliance with the GDPR.

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