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Oscilar Logo Oscilar · IT - Software Development

Fraud & AML Data Analyst

· Job Posted February 18, 2026
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Job Description

Shape the future of trust in the age of AI. At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place. As a Data Analyst at Oscilar, you will be a trusted partner to our customers and will be responsible for providing the analytics, insights and recommendations to protect their business from fraudulent activities. As an early member of the product analytics team you will have great impact in building and scaling our managed services business.

Job Responsibility

  • Analyze large-scale transaction, account, and behavioral datasets to identify fraud, AML, and abuse patterns across: Onboarding (synthetic identity, fake accounts, mule risk), Account activity (ATO, session hijacking, social engineering), Payments (card-not-present fraud, ACH/wire fraud, crypto typologies)
  • Develop risk segmentation, cohorts, and KPIs (fraud rate, approval rate, loss rate, false positives)
  • Evaluate rule-based and ML-driven decision strategies and quantify performance trade-offs
  • Partner with customers to: Diagnose their fraud and AML pain points, Interpret model outputs, alerts, and decision logic, Design and refine risk strategies using our platform
  • Produce customer-facing analytics, dashboards, and readouts that translate data into actionable risk decisions
  • Act as a trusted analytics advisor for customers implementing or scaling fraud programs
  • Work closely with Product and Engineering to: Define data requirements and success metrics for new features, Provide feedback on model explainability, rule tooling, and case workflows, Identify gaps in data, signals, or product capabilities based on real customer usage
  • Support experimentation (A/B tests, challenger strategies, rule tuning)
  • Contribute to internal and external documentation, including: Fraud and AML best practices, Lifecycle risk frameworks, Playbooks for onboarding, ATO, and payment fraud
  • Help shape standardized analytics and reporting frameworks across customers

Requirements

  • 4+ years of experience as a data analyst, data scientist or a related field, with a focus on fraud prevention and/or anti-money laundering
  • Proficiency in Python and SQL
  • Knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection
  • Experience working with large datasets and handling data-related challenges such as data cleaning, data quality, and data transformation and feature engineering at scale
  • Excellent analytical and problem-solving skills, with the ability to derive actionable insights from complex data
  • Strong communication skills, with the ability to explain complex concepts and findings to both technical and non-technical audiences
  • Ability to work independently and collaboratively in a fast-paced, dynamic startup environment

Nice to have

  • Experience in the fintech, marketplaces, or financial services industry
  • Knowledge of current fraud tactics and trends, as well as experience with fraud detection tools and systems

What we offer

  • Competitive salary and equity packages, including a 401k
  • Remote-first culture — work from anywhere
  • 100% Employer covered health, dental, and vision insurance with a top tier plan for you and your dependents (US)
  • Unlimited PTO policy
  • AI First company
  • both Co-Founders are engineers at heart
  • and over 50% of the company is Engineering and Product
  • Family-Friendly environment
  • Regular team events and offsites
  • Unparalleled learning and professional development opportunities
  • Making the internet safer by protecting online transactions
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