C2C jobs
Role: Discovery & GenAI Model Lead Consultant
Location: Remote
Contract
Lead discovery: Map current-state bordereaux processes end-to-end (intake → validations → reconciliations → approvals → exports to reinsurers) and adjacent flows (cession logic, losses, recoveries).
Define rulebooks: Elicit and document validation rules (field, cross-table, period roll-forward, totals, currency/FX, date sanity, ceded share, attachment/exhaustion), severity, and exception paths.
Design target state: Draft the solution blueprint—systems, integrations (Guidewire/Duck Creek/EDW/S3/SharePoint), data contracts, controls, and human-in-the-loop steps.
Controls & auditability: Define maker/checker, approval matrices, audit logs, and evidence bundles for internal audit and reinsurer queries.
Regulatory alignment: Ensure outputs support US GAAP/LDTI reporting needs; understand IFRS 17/Solvency II implications at Group; align to NAIC guidance; document retention & data-privacy constraints.
KPI & ROI framing: Set up baseline and target metrics (auto-validation %, time-to-export, error/rework rate, reinsurer query rate, cycle time) and build the pilot scorecard.
Stakeholder management: Facilitate workshops across reinsurance ops, finance, IT/integration, compliance, and underwriting; convert decisions into actionable backlog.
Pilot readiness: Write user stories, data requirements, sample sets, UAT scripts, and acceptance criteria; support change management and training materials.
Must-have experience
8–12+ years in commercial/industrial insurance across multiple lines: Property, Casualty/GL, Marine (cargo/hull), Engineering/CAR/EAR, Cyber.
Demonstrated bordereaux expertise (ceded premium, losses paid/incurred, recoveries, aggregates, slip wording impacts, reinsurer templates).
Strong finance/actuarial literacy (earned vs. written, IBNR concepts, cession mechanics, FX, period roll-forward).
Regulatory & controls: US GAAP/LDTI, NAIC statutory context; awareness of IFRS 17/Solvency II at group; SOX-style control design; audit evidence and retention.
AI/ML for ops: Practical experience shaping LLM/GenAI use cases—prompt engineering, RAG/retrieval design, confidence thresholds, redaction/masking, fallback to rules.
Tooling: SQL for validation prototypes; familiarity with Python helpful; exposure to workflow/orchestration (n8n, Control-M, Airflow) and ticketing (Jira/ServiceNow).
Excellent facilitation and writing—able to turn a 90-minute workshop into crisp rulebooks, diagrams, and acceptance criteria.
Nice to have
Reinsurance market experience from broker or carrier side (e.g., London Market, slip/binder nuances).
Experience with IFRS 17 CSM data needs and risk adjustment disclosures (awareness level is fine).
Prior work on claims leakage/fraud signals and underwriting triage with AI.
Exposure to data quality frameworks and lineage (e.g., Great Expectations, Collibra).
To apply for this job email your details to amer@mynasolutions.com