Fraud Detection Specialist | Snowflake

Fraud Detection Specialist — Full Role Description

A Fraud Detection Specialist identifies, prevents, and investigates fraudulent activity across transactions, accounts, user behavior, and systems. The role blends analytical investigation, real‑time risk monitoring, and cross‑functional coordination to reduce losses and protect customers and the business.

Monitor real‑time transactions and account activity; assess alerts, block or release decisions, and trigger additional verification when needed.

Conduct end‑to‑end investigations: gather evidence, reconstruct timelines, identify modus operandi, document findings in case systems.

Analyze trends in chargebacks, disputes, and incidents to refine rules, thresholds, and model features; reduce false positives.

Operate and tune fraud tools: risk scoring systems, device/behavioral intelligence, rules engines, and ML‑based detectors; propose new logic.

Produce dashboards and reports on fraud metrics, losses, recovery, and emerging patterns; brief leadership and stakeholders.

Collaborate with payments, risk, security, compliance/AML, SOC, and customer support; elevate high‑severity cases and coordinate actions.

Contribute to policy and process design: detections, reviews, KYC/KYB controls, dispute handling, and loss recovery procedures.

Support remediation and recovery efforts: transaction reversals, account actions, customer outreach and preventive control rollout.

Track emerging threats (account takeover, synthetic IDs, mule networks) and advise on control gaps across products and processes.

Lower fraud losses and chargeback rates via faster, more precise interdiction.

Reduced false positives and better customer experience through improved scoring and tuning.

Clear, auditable investigations with timely, actionable reporting.

Proactive controls that address new fraud vectors before they scale.

Data analysis: SQL, Excel/BI, familiarity with log and event data; able to spot anomalies and links in large datasets.

Fraud platforms: experience with real‑time monitoring, rules engines, device/behavioral risk, identity verification, and chargeback tooling.

Investigation: evidence collection, chain‑of‑custody awareness, case documentation, interviewing, and writing defensible reports.

Communication: concise escalation notes, stakeholder briefings, and cross‑team coordination under time pressure.

Domain knowledge: card‑not‑present/payments, e‑commerce and banking fraud typologies, disputes/chargebacks, compliance and AML touchpoints.

Collaboration:

partnering with fraud ops, risk, product, engineering, compliance, and customer care to operationalize controls.

Triage and review queued alerts; prioritize high‑risk cases.

Deep‑dive investigations using device, behavioral, historical, and network data; decide block/release/escalate.

Review dashboards for spikes, drift, or new patterns; propose rules or threshold changes.

Coordinate with payments/ops on disputes and reimbursements; sync with security/compliance on significant incidents.

Summarize trends and recommendations for management.

Machine learning: supervised/unsupervised detection, risk scoring, feature engineering, model performance and drift monitoring.

Streaming and real‑time decisioning: low‑latency pipelines to evaluate transactions in milliseconds.

Graph/network analytics: uncover mule rings, shared devices, collusive merchant/affiliate schemes.

Account takeover, identity theft, synthetic identity, payment card fraud, merchant/affiliate abuse, chargeback fraud, refund abuse, promotion abuse, bot‑driven abuse, and social engineering impacts.

Progression into Fraud Strategy, Risk Analytics, Payments Risk, Threat Intelligence, AML/Financial Crime, or Security Operations leadership.

Rapid growth in digital payments and online services has expanded fraud attack surfaces. Effective specialists combine domain knowledge, analytics, and fast operations to reduce losses while minimizing customer friction, preserving trust and growth.

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