Fraud & AML Data Analyst

About Oscilar

At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform, relied upon by banks, fintechs, and digitally native organizations to manage fraud, credit, and compliance risk. If you are passionate about solving complex problems and making the internet safer, this is your place.

Our mission-driven teams consist of industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer. We believe in extreme ownership, empowering you to take responsibility, move fast, and make decisions that drive our mission forward. Your work will shape how modern finance detects fraud and manages risk.

Job Description

As a Fraud & AML Data Analyst at Oscilar, you will be a trusted partner to our customers, responsible for providing the analytics, insights, and recommendations necessary to protect their businesses from fraudulent activities. As an early member of the product analytics team, you will have significant impact in building and scaling our managed services business.

Responsibilities

Fraud & AML Analytics

• 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), and 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.

Customer Risk Strategy & Enablement

• 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.

Product Collaboration

• 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).

Thought Leadership & Documentation

• Contribute to internal and external documentation, including fraud and AML best practices, lifecycle risk frameworks, and 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, 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.

Preferred Qualifications

• 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 Success Looks Like

• Customers use your insights to materially improve fraud loss, approval rates, or operational efficiency.
• Product teams rely on your analyses to prioritize features and data investments.
• You help establish our platform as a trusted risk partner, not just a tooling provider.

Benefits

• Compensation: Competitive salary and equity packages, including a 401k.
• Flexibility: Remote-first culture — work from anywhere (US).
• 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.

Key skills/competency

• Fraud Prevention
• AML Compliance
• Data Analysis
• SQL
• Python
• Machine Learning
• Risk Strategy
• Data Transformation
• Analytical Skills
• Communication Skills