3 months ago
Remote, United States +2 moreSenior / Staff+
H1B sponsor
Base Salary
$170k - $230k/yr
Responsibilities
- Surface emerging fraud patterns with Trust and Safety Architecture and Data Science teams and escalate or proactively address them.
- Analyze data to create sharper signals, configurations, decisioning logic, dashboards, and fraud models.
- Work directly with customers, partners, and prospects across different risk and business priorities.
- Investigate false positives, coverage gaps, vulnerabilities, anomalies, and systemic fraud issues using raw event streams.
- Lead forensic investigations during fraud spikes and produce remediation-focused reports.
- Contribute to detection frameworks, investigative tooling, internal playbooks, and product roadmap recommendations.
Requirements
- 5–8 years of experience in fraud, trust and safety, risk, or a closely related data science domain.
- Strong SQL and Python skills and experience analyzing large-scale behavioral or transactional datasets.
- Strong understanding of machine learning concepts applied to fraud, including classification models, feature engineering, precision/recall tradeoffs, threshold calibration, and score drift.
- Ability to communicate technical findings to technical and non-technical stakeholders through reports and presentations.
- Customer-facing experience and the ability to account for differing business priorities.
- Preferred experience with fraud detection platforms, LLM APIs, prompt engineering, agentic workflows, real-time event processing systems, and rules-based decisioning.
- Preferred background in payments, e-commerce, fintech, marketplaces, or account security fraud.
- Prior forward deployed, staff engineering, or embedded consulting experience at a technical product company is preferred.
- Computer Science, Data Science, Mathematics, Statistics, Information Systems, or Economics degree or equivalent is preferred.
Benefits
- Some travel may be required.
- Sift describes its workplace as diverse, equitable, and inclusive.
About Sift
Sift builds a cloud-based fraud prevention and risk scoring platform for online businesses, using machine learning to stop payment fraud, account abuse, and chargebacks. The privately held company was founded in 2011 and is headquartered in San Francisco. Its software is used by brands including Hertz, Yelp, and Poshmark, and is sold as a B2B SaaS suite integrated into commerce, payments, and identity workflows.