Quantitative Modeler, ALM & Insurance Analytics

Talcott Financial Group

$100K — $180K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Degree in quantitative finance or actuarial designation
  • Minimum of 1 year in quantitative asset modeling and AI applications
  • Strong mathematical skills with knowledge of fixed income pricing models and derivatives
  • Hands-on experience with Generative AI and machine learning
  • Technical skills in Python, NumPy, pandas, Fast API, and Azure cloud services
  • Strong communication skills for translating complex data insights
  • Demonstrated ability to manage multiple deliverables and drive process improvements

Responsibilities

  • Develop asset and liability models for self-service ALM forecasting
  • Create optimization strategies for hedging and capital efficiency
  • Implement anomaly detection for model validation
  • Build and maintain Python services for asset modeling
  • Ensure best practices in code review and CI/CD
  • Contribute to validation and reconciliation frameworks
  • Develop AI-assisted tools for documentation and anomaly explanation
  • Collaborate with teams to establish AI governance and validation

Benefits

  • Access to a newly formed AI Lab within the actuarial department
  • Opportunity to work on cutting-edge AI-driven business applications
  • Engagement in a results-oriented, high-performance environment
  • Professional development opportunities in quantitative modeling and AI
  • Collaborative work with cross-functional teams in Risk and Compliance
  • Potential for project leadership experience and ownership of processes
Full Job Description
Quantitative Modeler, ALM & Insurance Analytics

Overview:

Our Quantitative Modeling Analyst position will support the development of hands-on artificial intelligence (AI) engineering strategies that will strengthen the organization's asset and liability modeling capabilities. The strategy will allow us to modernize how Talcott values, projects, manages, and explains its wide variety of asset intensive liabilities. The Quantitative Analyst will assist in the development of self-service applications including chat experiences for investments, ALM, finance, and ERM users while remaining grounded in fixed income, derivatives, and ALM analytics. This opportunity will be a part a newly formed "AI Lab" within the actuarial department to accelerate the development of AI-driven business applications, asset modeling, and engineering to deliver generative and agentic AI capabilities that accelerate model production, automate documentation and controls.

Responsibilities:

  • Develop asset and liability models that support self-service ALM forecasting for Actuarial, Finance, and Risk users, including prepayment, credit migration, and default modeling.
  • Develop optimization approaches for SAA, hedging, capital efficiency, and surplus generation
  • Implement anomaly detection for valuation QA and model validation.
  • Build and maintain Python services integrating AXIS, KRM, QuantLib, and internal platforms
  • Follow best practices in version control, CI/CD (continuous integration/continuous deployment) and code review
  • Contribute to validation, controls and reconciliation frameworks.
  • Build self-service chat tools, LLM (large language model) based auto-documentation for governance and audit, AI-assisted reconciliation and anomaly explanation, and RAG (retrieval-augmented generation) solutions grounded in actuarial methods, regulatory guidance, and prior results.
  • Partner with Risk, Compliance, and IT to establish AI governance, safety, validation, and human-in-the-loop controls.
  • Stay up to date with technological advancement in AI tools and applications, and continuous development of potential use cases for the company.


Qualifications:

  • Degree in quantitative finance or actuarial designation
  • Minimum of 1 year of experience with quantitative asset modeling and AI applications
  • Strong mathematical and analytical skills with working knowledge of fixed income asset classes, pricing models, and derivatives
  • Progress toward an ASA or FSA is a plus
  • Demonstrated experience applying quantitative models to business challenges
  • Hands-on exposure to Generative AI, agentic workflows, chat assistants, and machine learning
  • Technical experience requirements: Python, NumPy, pandas, Fast API, Azure cloud services
  • Demonstrated ability to take ownership of processes and drive improvements independently
  • Experience providing project oversight or leading components of projects is a plus
  • Strong communication skills, with the ability to translate complex analysis into clear, actionable insights for senior stakeholders
  • Attention to detail and ability to manage multiple deliverables
  • Strong analytical and problem-solving skills, with demonstrated experience working with complex datasets and reporting frameworks
  • Results-oriented with a demonstrated ability to work under tight deadlines in a high-performance environment.


Compensation:

The annualized base pay range is mainly based on an evaluation of comparable positions in the external market. The actual base pay could vary and may be above or below the listed range. The base pay is based on factors including but not limited to experience, competence, and demonstration of proficiencies essential for the role. The base pay is just one component of Talcott's total annual compensation for employees. Other compensation may include annual bonuses, long-term incentives, and recognition. The salary for this role is: $100,000-$180,000.

Compensation:

This range represents the minimum and maximum annual base salary we reasonably expect to pay for this role at the time of posting. The actual base pay could vary and may be above or below the listed range. The base pay is based on factors including but not limited to experience, competence, and demonstration of proficiencies essential for the role. The base pay is just one component of Talcott's total annual compensation for employees. Other compensation may include annual bonuses, long-term incentives and recognition.

*This role is not eligible for visa sponsorship. Applicants must be authorized to work in the United States on a full-time basis without current or future visa sponsorship.

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