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Actuarial Forecasting Lead

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Onsite

Actuarial Forecasting Lead

IMR Soft LLC

Actuarial Forecasting Lead

Skills

Data ScienceMachine LearningAISupply Chain

12 days ago

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Important information


Contract type:

Freelance / Contract

Location:

United States

Work mode:

Onsite

Published on:

20 October 2026

What they need


Role: Actuarial Forecasting Lead

Location: Remote US

Duration: 12 Months

Description:

12-15 years experienced Actuarial Forecasting Lead who understands claims behaviour, loss development and the financial performance of insurance and protection products. The person should be able to work closely with actuarial, finance and technology teams to strengthen claims projections, loss estimates and actuarial modelling capabilities.

Experience:

  • Strong experience in actuarial modelling, claims frequency and severity analysis, loss ratio projections and claims cost estimation.
  • Good understanding of extended warranty, device protection, service contracts or specialty insurance products.
  • Experience in claims reserving, loss development analysis and ultimate loss projections.
  • Hands on experience in building and reviewing actuarial models using historical claims experience, exposure data, product mix and cost assumptions.
  • Understanding of repair and replacement costs, claim incidence rates, product failure patterns and their impact on loss projections.
  • Experience with actuarial and analytical tools.
  • Exposure to statistical modelling, and AI ML techniques applied to claims and loss estimation.
  • Experience working with actuarial, claims, underwriting and finance teams.

Responsibilities:

  • Review existing actuarial forecasting models, methodologies and assumptions used to project warranty claims, device failures and replacement demand.
  • Analyse historical claims, failure rates, product behaviour, repair and replacement patterns to understand the factors influencing future claims volumes.
  • Assess the reliability of actuarial forecasts and identify gaps in modelling approaches, data quality and underlying assumptions.
  • Evaluate and recommend suitable statistical, actuarial and predictive modelling techniques to improve forecast accuracy.
  • Work with actuarial, supply chain, data science and engineering teams to improve forecasting models and ensure their outputs meet supply chain planning needs.
  • Validate forecast results through actual-versus-expected analysis, back-testing and scenario analysis.
  • Lead functional discussions, model validation, and business acceptance of the forecasting solution.

Qualifications:

  • Bachelor's or Master's degree in Actuarial Science, Statistics, Mathematics or a related quantitative discipline.
  • Professional actuarial qualifications or progress towards actuarial certification would be an added advantage, but are not mandatory.

Practical experience in actuarial modelling, claims forecasting and applying actuarial projections to business planning is essential

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