Oscilar · 3 weeks ago
Fraud & AML Data Analyst
United States
Full-time
Remote
Mid, Senior Level
4+ years expOscilar is building the most advanced AI Risk Decisioning™ Platform to help organizations manage their fraud, credit, and compliance risk. The Data Analyst will analyze large datasets to identify fraud patterns and partner with customers to develop risk strategies, ultimately contributing to the safety of online transactions.
Cyber SecurityOperating SystemsSecurity
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
Qualification
Required
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
Preferred
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
Benefits
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
Company
Oscilar
The smartest way to make risk decisions.
51-200 employees
H1B Sponsorship
Oscilar has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (9)
2024 (3)
2023 (2)
2022 (1)
Funding
Current Stage
Growth StageTotal Funding
$20M2021-07-05Series A· $20M
Leadership Team
Neha Narkhede
Co-Founder & CEO
Recent News
MarketScreener
2025-12-12
2025-12-11
Company data provided by crunchbase