Fraud & Risk Management Analyst (Payments, Neo-Banking & Crypto)

Were hiring a Fraud & Risk Management Analyst with deep domain expertise in banking or payments (crypto exposure strongly preferred). You will transform raw data into actionable insightsdiscovering patterns, designing fraud rules & business logic, and partnering with Data/ML to continuously train and improve models. Your work will directly lower fraud losses, increase approval rates, and protect customers across markets.

What Youll Do

• Transaction Monitoring & Detection

• Analyze production streams (web, mobile, API, POS) to uncover fraud patterns (account takeovers, mule networks, triangulation, friendly fraud, synthetic IDs, bot abuse, velocity/structuring, BIN/range abuse, chargeback rings).

• Design, simulate, and deploy risk rules (pre-auth & post-auth) with thresholds, risk scores, and step-up flows; own rule governance and drift checks.

• Crypto Risk

• Identify crypto-specific typologies (bridging/mixing, peel chains, sanctioned counterparties, wash trading signals, dusting); define controls for VASP/Travel Rule workflows.

• Model Partnership

• Translate patterns into features/labels; curate training/evaluation datasets; review model outputs (precision/recall/AUC), and recommend thresholding & orchestration with rules.

• Decisioning & Orchestration

• Tune policy stacks (allow/deny/review), waterfall logic, step-up KYC/KYB, device/behavior checks, and 3-DS/SCA strategies to balance loss vs. conversion.

• Investigations & Casework

• Conduct in-depth analyses, create narrative memos, and recommend mitigations; support chargeback defense and dispute evidence packages.

• Compliance Alignment

• Partner with Compliance on KYC/KYB, AML/CFT, STR/SAR triggers, sanction screening, GDPR/India DPDP Act/PCI-DSS hygiene.

• Impact & Reporting

• Own and publish weekly dashboards: BPS fraud rate, authorization rate, false-positive rate, manual review rate, recovery %, chargeback rate by scheme/rail.

What Youll Need (Must-Haves)

• 510+ years in Fraud/Risk within a bank or payments company (issuer, acquirer, PSP, gateway, or neo-bank).

• Proven track record designing and shipping fraud rules and tuning risk engines in production.

• Hands-on with transaction data and advanced SQL; comfortable with Python/R for analysis (no heavy ML coding required, but strong analytical rigor is essential).

• Working knowledge of card & bank rails (auth flows, MCCs, BIN ranges, 3-DS/SCA, chargebacks/disputes, UPI/NPCI constructs, reconciliation).

• Familiarity with crypto risk signals and Travel Rule/VASP concepts.

• Strong grasp of metrics & trade-offs (loss vs. conversion, precision/recall, latency).

• Excellent written analysis: incident memos, runbooks, and executive summaries.

Nice to Have

• Exposure to tools/concepts like device fingerprinting, bot mitigation, graph/link analysis, velocity stores, case management systems.

• Experience with real-time data stacks (Kafka/Kinesis), feature stores, or SIEM; basic knowledge of MLOps/experimentation.

• Prior work with sanctions screening, name matching, and geolocation/IP intelligence.

What Youll Work With

• Platforms: Verafye (Fraud & Risk)

• Data: Real-time transaction streams across cards/UPI/bank rails/wallets + blockchain signals

• Team: Risk Engineers, Data Scientists, Product Managers, and Platform Engineering

• Success Looks Like (First 6 Months)

• Ship 23 high-impact rule packs cutting targeted fraud typologies by 3050% with 10% incremental false positives.

• Improve auth/approval rate by 100200 bps via smarter step-ups and thresholding.

• Establish a fraud intel operating cadence (dashboards, alerts,