Actuarial Forecasting Lead

TMS, LLC

. Build and validate probabilistic claims-frequency, cohort, and exposure models using insured-device populations, claims history, policy conditions, product mix, device age, churn, and external drivers .

Posted 10/30/2026full-timeRemote • New York • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in developing and validating insurance predictive-risk models, with strong proficiency in Python and SQL for actuarial modeling and financial risk assessment. Ability to communicate complex valuation findings and collaborate across functions to influence decision-making in inventory risk management.

Highest-signal resume keywords

Actuarial Credential (ACAS, FCAS, ASA, FSA)Insurance Predictive-Risk ModelingPython ProficiencySQL ProficiencyStochastic Simulation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Insurance Claims-Frequency ModelingExposure-Based ModelingFinancial Risk ModelingCalibrationSensitivity AnalysisTail-Risk MeasurementMonte Carlo SimulationQuantitative Decision SupportValuation of Supply ContractsData Validation

Soft Skills

Strong Ethical JudgmentCross-Functional CollaborationCommunication of Uncertainty

Certifications & Qualifications

ACASFCASASAFSACERA

Industry Keywords

Inventory Risk ManagementSupply ChainFinanceActuarial ScienceQuantitative FinanceMarket Data AnalysisRisk Valuation MethodologyPhysical-Market Contract EconomicsAsset RiskDecision-Ready Forecasts

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Build and validate probabilistic claims-frequency, cohort, and exposure models using insured-device populations, claims history, policy conditions, product mix, device age, churn, and external drivers
Produce calibrated time-phased demand distributions by client, program, model family, and horizon
Distinguish insured claims incidence from repair, replacement, substitution, and SKU-level fulfillment outcomes
Backtest assumptions, explain forecast error, and partner with Data Science to translate predicted claims into decision-ready forecasts
Model depreciation, residual values, recoverability, liquidation discounts, price volatility, liquidity, obsolescence, and concentration across mobile-device inventory
Assess claims, future supply, secondary-market prices, repair yields, and inventory holdings using stochastic scenarios, Monte Carlo simulation, expected loss, tail-risk metrics, and stress tests
Provide forward-looking risk estimates and evidence for Finance-owned monthly inventory reserve assessments
Price and assess physically settled forward purchases and sales, structured supply or offtake agreements, volume-flex commitments, and deliverable purchase/sale options
Model strike or delivery prices, optional quantities, exercise timing, specifications, grading, counterparty performance, delivery terms, and embedded optionality
Integrate demand and market-value simulations to evaluate risk-adjusted buy, hold, repair, transfer, sell, and hedge decisions
Quantify working capital, stockout exposure, purchasing premiums, expected depreciation, and tail-risk tradeoffs to propose exposure limits and hedging thresholds
Write reproducible Python and SQL models and document data lineage, parameters, validation, backtesting, assumption changes, and model limitations
Establish common risk terminology, influence planning and procurement decisions, and help develop enterprise inventory-risk methodology
Communicate probability and valuation findings to Supply Chain, Finance, Actuarial, Risk, and executive stakeholders
Serve as senior technical authority for actuarial and risk valuation methodology; mentor colleagues and coordinate cross-functional working groups

Requirements

What you’ll need

Hold an active professional actuarial credential (ACAS, FCAS, ASA, FSA, or recognized international actuarial equivalent)
A CERA designation alone does not replace the base actuarial credential
Demonstrated hands-on professional experience developing or materially validating insurance claims-frequency, exposure-based, or comparable insurance predictive-risk models
Demonstrated hands-on experience valuing or pricing physically delivered forward, offtake, volume-flex, commodity, or asset supply contracts with meaningful delivery obligations or embedded optionality; theoretical coursework alone is insufficient
8+ years of relevant experience spanning actuarial modeling, enterprise or asset risk, physical-market contract economics, and quantitative decision support
Bachelor's degree in actuarial science, statistics, mathematics, quantitative finance, economics, engineering, or a closely related discipline
Advanced stochastic simulation, financial risk modeling, calibration, sensitivity analysis, tail-risk measurement, and evaluation of correlated exposure
Strong hands-on Python and SQL proficiency; ability to design models, independently inspect model code, and explain methods and commercial implications
Demonstrated ability to work with incomplete market data, communicate uncertainty, and navigate cross-functional decisions with strong ethical judgment

Benefits

Comp & perks

Confidential handling of all information according to EEO guidelines