Senior Data Scientist, Fraud & Risk Analytics

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📅  Posted 18 days ago 📍 Germany, United States 💵 not specified
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Job Description

About the team:

The Fraud and Risk Analytics team is responsible for detecting and preventing fraudulent activities that may endanger the health of the Worldcoin 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 Worldcoin’s long-term success.

About the Opportunity:

As our first dedicated data scientist on the Fraud Team, you will employ a data-driven approach towards mitigating fraudulent activity in the Worldcoin network while ensuring a frictionless online experience for Worldcoin’s users. You will be responsible for (1) maintaining and expanding the data for effective fraud analytics, (2) owning data-driven monitoring and alerting related to fraud, and (3) uncovering impact and root causes in forensic analysis through advanced analytics methods. You will work collaboratively with almost every team in the company, including Product, Market Operators, Trust & Safety, AI, Orb Software and Data Science. Your work will directly impact the health and sustainability of the Worldcoin network.

In this role, you will:

  • Develop a deep understanding of the data landscape relevant for fraud and risk analytics (from Market Operations, Product, Customer Support, Blockchain, etc.) 
  • Investigate suspected fraud causes as they occur, together with fraud strategists and fraud analysts, by translating anecdotal evidence into detectable patterns in our data and surfacing these patterns in the data
  • Perform data-driven forensic analysis of fraud events, together with fraud strategists and fraud analysts, for the purpose of identifying and consistently categorizing the root cause of fraud events (observed or attempted)
  • Develop and deploy advanced analytical methods to improve our fraud detection and prevention capabilities (e.g., statistical inference, machine learning or graph analysis) 
  • Develop and optimize heuristics to drive programmatic fraud strategies (e.g., synchronous blocking of actions at key risk moments or blocklisting and whitelisting) to effectively prevent fraud while minimizing false positives
  • Defining and implementing the most appropriate metrics and indicators to create transparency and track the effectiveness of our defensive strategies through charts, dashboards, and alerts 

About You:

  • Master’s degree in a quantitative field like mathematics, economics, computer science, statistics, or similar; PhD a plus
  • 5+ years of hands-on work experience as a data scientist
  • Demonstrated ability to perform root cause analysis for data problems with a high level of rigor and attention to detail
  • Advanced knowledge of SQL
  • Programming experience in at least one high-level programming language (e.g., Python)
  • Experience in data wrangling across multiple disparate data sources
  • Practically oriented and “getting-the-job-done” mindset
  • Thriving in a fast-paced and continuously evolving environment
  • Experience with either of the following is a plus: fraud investigations and incident response procedures, fraud/risk engine and experience tuning fraud rules, digital payments and/or payment networks, graph databases (e.g., Neo4j) and graph learning, working with Blockchain data
  • Experience with business intelligence tool like Metabase, Tableau, or Looker a plus
  • A background in machine learning (i.e., constructing ML models, feature engineering, hyperparameter tuning) is a plus

This role is available at the Senior or Staff level, depending on experience.

Location:

Berlin or San Francisco. If located elsewhere, candidates are expected to relocate to one of these two locations.