Fraud & AML Data Analyst
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Job Description
Data Analyst responsible for fraud and AML analytics at Oscilar's advanced AI Risk Decisioning platform. Collaborating with customers and product teams to enhance fraud detection strategies.
Responsibilities:
- 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.
Benefits:
- Compensation: Competitive salary and equity packages, including a 401k
- Flexibility: Remote-first culture — work from anywhere
- Health: 100% Employer covered health, dental, and vision insurance with a top tier plan for you and your dependents (US)
- Balance: Unlimited PTO policy
- Technical: AI First company; both Co-Founders are engineers at heart; and over 50% of the company is Engineering and Product
- Culture: Family-Friendly environment; Regular team events and offsites
- Development: Unparalleled learning and professional development opportunities
- Impact: Making the internet safer by protecting online transactions
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