Senior Actuarial Analyst, Predictive Modeling
Quick Summary
Overview Looking for a driven, inventive, and highly technical actuarial candidate to build and maintain tools that support modeling and actuarial workflows across multiple lines of business.
Looking for a driven, inventive, and highly technical actuarial candidate to build and maintain tools that support modeling and actuarial workflows across multiple lines of business. This person will sit within the Actuarial Predictive Modeling tools team and focus on developing and maintaining applications, automations, and infrastructure that make reviewing and monitoring predictive models more effective and transparent. Just as importantly, this role requires someone with actuarial judgment who can understand the business and modeling reasons behind the tools being built, help identify where new tools or enhancements would add value, and ensure those solutions are grounded in real actuarial needs. You will design both backend and frontend portions of these tools with an eye toward scalability, maintainability, and utility, working with colleagues across actuarial, underwriting, and data science.
AmTrust is an innovative, customer-centric leader in commercial insurance. We're looking for someone who can navigate complex data and codebases, contribute to multiple concurrent projects, and proactively identify opportunities to improve how actuarial work gets done. The right candidate will not only build tools, but also help interpret their output, surface meaningful insights and limitations, and communicate what the results mean to both technical and non-technical audiences.
Responsibilities
~1 min read- →Build and maintain actuarial tools and applications — including interactive Shiny and Streamlit apps, Power BI dashboards, and data pipelines — that support model review, model interpretation, data validation, reporting, and decision-making across lines of business
- →Develop process automations to streamline recurring workflows, such as automated data checks for reporting, and monitoring tools for data drift and model drift
- →Understand and refactor existing codebases to improve performance, maintainability, and documentation; manage multiple tools and projects concurrently
- →Collaborate with data science, actuarial, and business teams to translate analytical needs into well-designed tools and dashboards, and proactively identify opportunities for new tools or enhancements
- →Evaluate and adopt emerging technologies, including AI/Copilot capabilities
- →Communicate results, tool capabilities, and tool output to technical and non-technical stakeholders, including explaining what results mean, where limitations exist, and how outputs should inform decisions
- →Foster strong coding and data operations best practices, including version control (Git), code review, and change management processes
Requirements
~2 min read- Bachelor's degree in Actuarial Science, Mathematics, Computer Science, Statistics, or related field
- 3+ years of actuarial experience, actively pursuing ACAS or FCAS
- 3+ years of hands-on experience in data exploration, manipulation, and visualization with either R or Python, with at least working familiarity with the other language
- Comfort with reading and writing complex SQL queries
- Experience with Git for version control and collaborative development
- Dashboarding experience in Power BI (including DAX), Shiny, Streamlit, or similar frameworks
- Strong grasp of statistical methods applied to insurance data, including the ability to identify and articulate data and modeling issues
- Experience identifying opportunities for workflow enhancements and successfully implementing changes or new tools to address them
- Ability to build trust and rapport across teams and create a collaborative, effective workplace
- Excellent problem-solving skills and attention to detail
- Demonstrated ability to experiment with and learn new technologies
Bonus Qualifications:
- Experience with Posit Connect and Posit Workbench
- Experience creating packages in R or Python
- Experience optimizing code including R, Python, and SQL queries
- End-to-end experience building predictive models, including some involvement in implementation and deployment
- Familiarity with model interpretability tools/packages (SHAP, tree-based interpretation, etc.)
- Experience with data modeling in Power BI / Microsoft Fabric
The expected salary range for this role is $60K- $118K/year.
Please note that the salary information shown above is a general guideline only. Salaries are based upon a wide range of factors considered in making the compensation decision, including, but not limited to, candidate skills, experience, education and training, the scope and responsibilities of the role, as well as market and business considerations.
What We Offer
~1 min readAmTrust Financial Services offers a competitive compensation package and excellent career advancement opportunities. Our benefits include: Medical & Dental Plans, Life Insurance, including eligible spouses & children, Health Care Flexible Spending, Dependent Care, 401k Savings Plans, Paid Time Off.
AmTrust strives to create a diverse and inclusive culture where thoughts and ideas of all employees are appreciated and respected. This concept encompasses but is not limited to human differences with regard to race, ethnicity, gender, sexual orientation, culture, religion or disabilities.
AmTrust values excellence and recognizes that by embracing the diverse backgrounds, skills, and perspectives of its workforce, it will sustain a competitive advantage and remain an employer of choice. Diversity is a business imperative, enabling us to attract, retain and develop the best talent available. We see diversity as more than just policies and practices. It is an integral part of who we are as a company, how we operate and how we see our future.
Location & Eligibility
Listing Details
- Posted
- May 18, 2026
- First seen
- May 18, 2026
- Last seen
- May 19, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 49%
- Scored at
- May 18, 2026
Signal breakdown
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