Risk Operations AI Specialist
🇮🇳 India | 🇸🇬 Singapore | 🇯🇵 Japan | 🇹🇭 Thailand | 🇨🇳 China | 🇮🇩 Indonesia | 🇧🇩 Bangladesh | 🇮🇷 Iran | 🇯🇴 Jordan | 🇰🇿 Kazakhstan | 🇲🇾 Malaysia | 🇳🇵 Nepal | 🇵🇰 Pakistan | 🇵🇭 Philippines | 🇰🇷 South Korea | 🇱🇰 Sri Lanka | 🇹🇼 Taiwan | 🇹🇷 Turkey | 🇻🇳 Vietnam | 🇱🇧 Lebanon | 🇲🇲 Myanmar | 🇱🇦 Laos | 🇾🇪 Yemen | 🇲🇻 Maldives | 🇴🇲 Oman
Management
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Machine Learning
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Analyst
Testing
Risk Operations AI Specialist
from 🇮🇳 India | 🇸🇬 Singapore | 🇯🇵 Japan | 🇹🇭 Thailand | 🇨🇳 China | 🇮🇩 Indonesia | 🇧🇩 Bangladesh | 🇮🇷 Iran | 🇯🇴 Jordan | 🇰🇿 Kazakhstan | 🇲🇾 Malaysia | 🇳🇵 Nepal | 🇵🇰 Pakistan | 🇵🇭 Philippines | 🇰🇷 South Korea | 🇱🇰 Sri Lanka | 🇹🇼 Taiwan | 🇹🇷 Turkey | 🇻🇳 Vietnam | 🇱🇧 Lebanon | 🇲🇲 Myanmar | 🇱🇦 Laos | 🇾🇪 Yemen | 🇲🇻 Maldives | 🇴🇲 Oman
Responsibilities:
Core Review Duties
- Review cases escalated by ROCA where confidence score falls below the auto-decision threshold, using AI-assisted signals within the unified case review UI (no multi-system switching)
- Make accurate pass / block / escalate decisions on a daily queue spanning KYC Audit, ATO investigation, Reset 2FA, POA Review, and Withdrawal anomaly case types etc.
- Escalate Key User cases (Priority ≥ 75) and high-risk patterns to Senior Agent / Team Lead with clear rationale documentation
- Maintain SLA compliance (<4h manual resolution time) while sustaining decision accuracy ≥ 98%
AI Feedback & Pipeline Contribution
- Label every reviewed case as TP / TN / FP / FN with structured root-cause annotations — this data directly feeds ROCA's continuous learning pipeline
- Identify recurring FP/FN patterns and route them through the correct feedback path:
- Type A — Feature weight bias → trigger model retraining / fine-tune
- Type B — Threshold miscalibration → update Decision Hub rules (with A/B validation)
- Type C — SOP gap or logic error → update SOP (version-tracked)
- Actively contribute to improving Precision (>95%) and Recall (>99%) targets by surfacing systematic signal failures to Data and Model teams
- Participate in regular AI model calibration sessions: review misclassification batches, validate ground truth, challenge decision thresholds with data
SOP & Knowledge Management
- Maintain and update Confluence SOP pages for assigned case types; SOP coverage rate target ≥ 80% (directly impacts ROCA first-pass accuracy)
- Flag SOP coverage gaps when ROCA's reasoning chain reveals unhandled scenarios; draft SOP additions for Team Lead review
- Onboard and calibrate BPO agents on AI-assisted review workflows; monitor BPO quality against automated QA benchmarks
Requirements:
- 2+ years in fraud review, risk operations, or KYC/KYB case management
- Hands-on experience with ATO (Account Takeover) detection and investigation
- Comfort working in AI-augmented workflows: you read model outputs, interpret confidence scores, and make decisions based on AI-generated signals rather than raw data alone
- Structured, precise written communication: you can document a root-cause annotation in <3 sentences that an ML engineer can act on
- Bilingual English/Mandarin is required to be able to coordinate with overseas partners and stakeholders.
- An operator's mindset toward AI tools: you leverage AI signals to make faster, better decisions — you master the tool rather than compete with it
Nice to have:
- Experience in crypto / Web3 / VASP risk environment; familiarity with blockchain transaction patterns (Sybil attacks, wash trading, mule account indicators)
- Exposure to ML model evaluation concepts: Precision, Recall, F1, confusion matrix — you don't need to build models, but you need to speak the language
- Familiarity with prompt engineering or LLM evaluation workflows; experience reviewing or testing AI-generated decisions at scale
- CAMS, CFE, or equivalent AML / fraud certification
- Prior involvement in SOP authoring, QA calibration, or BPO oversight for a risk operations team