Forward Deployed Engineer, Trust and Safety

About the role

Sift is building an AI‑powered fraud platform to make the internet safer. As a Forward Deployed Engineer in Trust and Safety you will work directly with customers and internal teams to detect, analyze, and mitigate online abuse at scale.

Key responsibilities

• Collaborate with Trust and Safety architects and data scientists to surface emerging fraud patterns and proactively take them down.
• Design and refine detection signals, configuration rules, and decision‑making logic across multiple verticals.
• Build dashboards, tune models, and create custom signals that help customers meet their risk and business goals.
• Investigate fraud spikes, trace attack sources, and produce forensic reports with remediation steps.
• Identify false‑positive sources, coverage gaps, and systemic vulnerabilities, then design and implement fixes.

Required profile

• 5–8 years of experience in fraud, trust & safety, risk, or a closely related data‑science domain.
• Strong SQL and Python skills; comfortable coding to answer analytical questions.
• Deep understanding of machine‑learning concepts applied to fraud detection (classification models, feature engineering, precision/recall trade‑offs, threshold calibration, score drift).
• Proven ability to analyze large‑scale behavioral or transactional datasets to uncover patterns and anomalies.
• Excellent communication skills for both technical and non‑technical stakeholders, including forensic reporting and executive presentations.
• Customer‑facing experience with the ability to adapt solutions to differing risk appetites.

Required skills

• SQL
• Python
• Machine Learning
• Classification models
• Feature engineering
• Precision/recall analysis
• Threshold calibration
• Score drift monitoring
• Large‑scale data analysis