POSITION OVERVIEWThis position, located in the Boston, MA or Des Moines, IA office, is a permanent role within the Model production team supporting the execution, testing and end-to-end production lifecycle of actuarial models for the Annuity and Life Insurance businesses. The candidate will execute and test models, prepare model inputs, review and analyze results within the control financial reporting processes.
In addition to core Model Production responsibilities, this role will serve as a hands-on technical resource for Python/PySpark-based data transformation, model-input generation, automation, data validation, and production controls. The role will help migrate and maintain production processes on modern actuarial data and workflow technology while improving reliability, transparency, and efficiency.
The candidate will work closely with Model Development, Valuation, Data, Transformation, and technology teams.
KEY RESPONSIBILITIESModel Production- Lead and perform accurate monthly and quarterly production runs using Integrate and MG-ALFA models to calculate US Statutory, Tax, US GAAP reserves, and other related actuarial balances.
- Prepare and validate model input files, including asset, liability, and scenario inputs.
- Review and analyze model results and investigate variances.
- Maintain evidence for SOX controls associated with production model runs.
- Conduct annual impact testing for potential assumption changes.
- Perform model runs to test model updates implemented by the Model Development team.
- Perform model runs to provide the Valuation team with reserve impacts from model changes and support the review and approval of those changes.
- Support analysis, including sensitivities, for statutory and GAAP balances and earnings impacts.
- Support audit and regulatory requests.
Python, Data Transformation, Automation, and Technical Support- Develop, maintain, and troubleshoot Python and PySpark ETL processes that transform source data into production-ready actuarial model inputs and support model-output and post-processing workflows.
- Maintain a clear source-to-model understanding for assigned production processes, including source data, mappings, reference data, transformation logic, model inputs, and key downstream dependencies.
- Implement routine transformation, mapping, and data-processing changes using established development and change-management standards; document business logic and maintain traceable change history.
- Build and enhance automated data-quality checks, reconciliations, exception handling, and production controls to improve completeness, accuracy, and transparency of model inputs and outputs.
- Use Git-based source control, branches, pull requests, peer review, and documented testing to manage Python/PySpark production changes in a controlled manner.
- Perform unit, regression, integration, and end-to-end testing of ETL and automation changes, including reconciliation to legacy or prior-period results where appropriate.
- Support migration of legacy IDM, Excel/VBA, or other manual production processes to Python/PySpark and automated workflows, with a focus on sustainable, reusable production solutions.
- Troubleshoot production issues across source data, transformations, model inputs, model execution, and outputs; partner with Data and Technology teams when issues involve enterprise data pipelines, infrastructure, or platform services.
- Support workflow orchestration, monitoring, and restart processes for automated actuarial production, including Dagster or comparable orchestration tooling as applicable.
QUALIFICATIONS- Bachelor's degree in Actuarial Science, Mathematics, Statistics, Finance, Computer Science, or a related field.
- Minimum ASA or equivalent designation.
- At least 5 years of actuarial experience in the life insurance and retirement industry,
- Direct work experience with or knowledge of life and annuity products, US Statutory and GAAP valuation.
- Experience with MG-ALFA, Integrate, Prophet, RAFM, Pathwise, or other actuarial modeling and valuation software.
- Strong hands-on Python programming skills are required, including the ability to read, develop, test, and troubleshoot production code.
- Working knowledge of PySpark and experience with ETL/data-transformation processes, large datasets, data validation, and reconciliations.
- Experience with Git/source control and basic software-development change-management practices, including branches, commits, pull requests, peer review, and controlled testing.
- Familiarity with workflow orchestration and cloud-based data-processing environments such as Dagster, AWS/EMR, or comparable technologies is preferred.
- Strong communication, technical, and analytical skills, with the ability to work effectively across Model Production, Model Development, Valuation, Data, and Technology teams.
- Ownership and continuous-improvement mindset, with personal accountability for the execution of goals and objectives.
- Innovative. Able to participate in the generation of new ideas and process improvements.
- Teamwork. Has a positive attitude and works well with others.
- Comfort using AI-powered tools to improve productivity and quality of work
- Curiosity about and openness to adopting emerging AI technologies in day-to-day workflows
- Ability to critically evaluate AI-generated outputs for accuracy and relevance
This is the expected annual base salary range for this Boston-based position. Actual salaries may vary based on factors, such as skill, experience, and qualification for the role. Employees may be eligible for a discretionary bonus, based on factors such as individual and team performance.
Base Salary Range
$130,000-$170,000 USD
This is the expected annual base salary range for this Iowa-based position. Actual salaries may vary based on factors, such as skill, experience, and qualification for the role. Employees may be eligible for a discretionary bonus, based on factors such as individual and team performance.
Base Salary Range
$130,000-$170,000 USD
