Actuarial Forecasting Lead

This is a fully remote position, open to applicants in New York.

📋 Description

• Develop and validate probabilistic models for claims frequency, cohorts, and exposure using data from insured-device populations, claims history, policy conditions, product mix, device age, churn rates, and external factors.

• Generate calibrated, time-phased demand distributions tailored to clients, programs, model families, and forecasting horizons.

• Differentiate between insured claims incidence and outcomes related to repair, replacement, substitution, and SKU-level fulfillment.

• Conduct backtesting of assumptions, provide explanations for forecast errors, and collaborate with the Data Science team to convert predicted claims into actionable forecasts.

• Model depreciation, residual values, recoverability, liquidation discounts, price volatility, liquidity, obsolescence, and concentration within mobile-device inventory.

• Evaluate claims, future supply, secondary-market pricing, repair yields, and inventory levels using stochastic scenarios, Monte Carlo simulations, expected loss calculations, tail-risk metrics, and stress testing.

• Deliver forward-looking risk assessments and supporting evidence for Finance's monthly inventory reserve evaluations.

• Analyze and price physically settled forward purchases and sales, structured supply or offtake agreements, volume-flex commitments, and options for purchase/sale.

• Model delivery prices, optional quantities, exercise timing, specifications, grading, counterparty performance, delivery terms, and embedded optionality.

• Combine demand and market-value simulations to assess risk-adjusted decisions regarding buying, holding, repairing, transferring, selling, and hedging.

• Measure working capital needs, stockout risks, purchasing premiums, expected depreciation, and tail-risk trade-offs to suggest exposure limits and hedging thresholds.

• Write reproducible models in Python and SQL, documenting data lineage, parameters, validation, backtesting, changes in assumptions, and model limitations.

• Establish standardized risk terminology, influence planning and procurement strategies, and contribute to the development of enterprise-level inventory risk methodologies.

• Communicate findings related to probability and valuation to stakeholders in Supply Chain, Finance, Actuarial, Risk, and executive leadership.

• Act as a senior technical authority for actuarial and risk valuation methodologies; mentor team members and coordinate cross-functional working groups.

⛳️ Requirements

• Possess an active professional actuarial credential (ACAS, FCAS, ASA, FSA, or an internationally recognized equivalent).

• A CERA designation does not substitute for the foundational actuarial credential.

• Proven hands-on professional experience in developing or significantly validating insurance claims-frequency models, exposure-based models, or comparable predictive-risk models.

• Demonstrated experience in valuing or pricing physically delivered forward contracts, offtake agreements, volume-flex contracts, commodity contracts, or asset supply contracts with substantial delivery obligations or embedded optionality; theoretical knowledge alone is not adequate.

• Over 8 years of relevant experience in actuarial modeling, enterprise or asset risk, physical market contract economics, and quantitative decision-making support.

• Bachelor’s degree in actuarial science, statistics, mathematics, quantitative finance, economics, engineering, or a closely related field.

• Advanced skills in stochastic simulation, financial risk modeling, calibration, sensitivity analysis, tail-risk measurement, and the evaluation of correlated exposures.

• Strong practical proficiency in Python and SQL; capability to design models, independently review model code, and articulate methods and commercial implications.

• Proven ability to work with incomplete market data, convey uncertainty, and navigate cross-functional decisions with a strong ethical foundation.

🏝️ Benefits

• Confidential management of all information in accordance with EEO guidelines.