Actuarial Analyst Resume Preview
- Prepared quarterly IBNR reserve estimates for 6 lines of business totaling $450M in gross reserves, using chain ladder, Bornhuetter-Ferguson, and Cape Cod methods with results reviewed and approved by the appointed actuary.
- Built a GLM-based pricing model in R for the commercial auto line that incorporated 25 rating variables, resulting in a rate indication of +8.2% that was filed with 12 state regulators and approved without objection.
- Automated the monthly loss ratio monitoring process in Python, replacing 40+ hours of manual Excel work per quarter with a script that pulls data from the data warehouse and generates formatted reports for 8 underwriting teams.
- Analyzed 5 years of claims data (200,000+ records) to identify adverse development trends in the workers' compensation book, flagging a $12M reserve deficiency 6 months before it would have appeared in standard actuarial reviews.
- Developed an experience rating tool in Excel/VBA for 500+ large commercial accounts, enabling underwriters to generate mod factors in 2 minutes instead of requesting them from the actuarial team with a 3-day turnaround.
- Supported the annual rate filing for personal auto insurance across 8 states, preparing 200+ pages of actuarial exhibits, trend analyses, and credibility calculations that met regulatory requirements and achieved a combined rate change of +5.1%.
- Created a Tableau dashboard tracking loss ratios, frequency, and severity trends across all P&C lines on a monthly basis, replacing static quarterly reports and giving leadership real-time visibility into emerging loss patterns.
- Performed a profitability analysis of the homeowners book by policy vintage and territory, identifying 3 underperforming segments responsible for $8M in annual underwriting losses that led to targeted rate increases and tighter underwriting guidelines.
- Modeled the financial impact of 4 proposed reinsurance treaty structures, estimating net retention, ceded premium, and expected recoveries under 1-in-50 and 1-in-100 year loss scenarios to support the CFO's reinsurance purchasing decision.
- Passed 4 actuarial exams (P, FM, IFM, STAM) while working full-time, maintaining exam study discipline alongside a full project workload and meeting all deliverable deadlines without exception.
- Collaborated with the data engineering team to validate the migration of actuarial data from a legacy AS/400 system to Snowflake, reconciling 10 years of policy and claims data across 15 tables with a variance threshold of less than 0.01%.
Languages & Frameworks: R, Python, SQL, Excel/VBA
Tools & Infrastructure: SAS, Actuarial Reserving, Loss Ratio Analysis, GLM Pricing Models
Methodologies & Practices: Arius/ResQ, Tableau
Executive Reporting and Forecasting System - Built a decision-support reporting workflow using R and validated data models. Consolidated fragmented reports into trusted dashboards that improved forecast accuracy and reduced manual reporting effort.
Data Quality and Pipeline Governance Initiative - Implemented validation checks, documentation, and ownership rules across datasets tied to Python, SQL, Excel/VBA. Reduced recurring data issues and gave stakeholders clearer definitions for key business metrics.
Associate of the Casualty Actuarial Society (ACAS) - in progress
SOA Exam P, FM, IFM, STAM passed
Professional Summary
Actuarial analyst with 3+ years of experience in property and casualty insurance, focused on reserving, pricing, and loss ratio analysis. Passed 4 SOA/CAS exams and proficient in R, Python, and actuarial modeling platforms with strong communication skills for presenting findings to underwriting leadership.
Key Skills
What to Include on a Actuarial Analyst Resume
- A concise summary that states your actuarial analyst experience level, strongest domain, and the business problems you solve.
- A skills section that mirrors the job description language for R, Python, SQL, Excel/VBA.
- Experience bullets that connect actuarial analyst, loss reserving, pricing models to measurable outcomes such as cost savings, faster delivery, better quality, or improved customer results.
- Tools, platforms, certifications, and methods that are current for data & analytics roles.
- Recent projects that show ownership, cross-functional work, and a clear result instead of generic responsibilities.
Sample Experience Bullets
- Prepared quarterly IBNR reserve estimates for 6 lines of business totaling $450M in gross reserves, using chain ladder, Bornhuetter-Ferguson, and Cape Cod methods with results reviewed and approved by the appointed actuary.
- Built a GLM-based pricing model in R for the commercial auto line that incorporated 25 rating variables, resulting in a rate indication of +8.2% that was filed with 12 state regulators and approved without objection.
- Automated the monthly loss ratio monitoring process in Python, replacing 40+ hours of manual Excel work per quarter with a script that pulls data from the data warehouse and generates formatted reports for 8 underwriting teams.
- Analyzed 5 years of claims data (200,000+ records) to identify adverse development trends in the workers' compensation book, flagging a $12M reserve deficiency 6 months before it would have appeared in standard actuarial reviews.
- Developed an experience rating tool in Excel/VBA for 500+ large commercial accounts, enabling underwriters to generate mod factors in 2 minutes instead of requesting them from the actuarial team with a 3-day turnaround.
- Supported the annual rate filing for personal auto insurance across 8 states, preparing 200+ pages of actuarial exhibits, trend analyses, and credibility calculations that met regulatory requirements and achieved a combined rate change of +5.1%.
- Created a Tableau dashboard tracking loss ratios, frequency, and severity trends across all P&C lines on a monthly basis, replacing static quarterly reports and giving leadership real-time visibility into emerging loss patterns.
- Performed a profitability analysis of the homeowners book by policy vintage and territory, identifying 3 underperforming segments responsible for $8M in annual underwriting losses that led to targeted rate increases and tighter underwriting guidelines.
- Modeled the financial impact of 4 proposed reinsurance treaty structures, estimating net retention, ceded premium, and expected recoveries under 1-in-50 and 1-in-100 year loss scenarios to support the CFO's reinsurance purchasing decision.
- Passed 4 actuarial exams (P, FM, IFM, STAM) while working full-time, maintaining exam study discipline alongside a full project workload and meeting all deliverable deadlines without exception.
- Collaborated with the data engineering team to validate the migration of actuarial data from a legacy AS/400 system to Snowflake, reconciling 10 years of policy and claims data across 15 tables with a variance threshold of less than 0.01%.
ATS Keywords for Actuarial Analyst Resumes
Use these terms naturally where they match your experience and the job description.
Role keywords
Technical keywords
Process keywords
Impact keywords
Recommended Certifications
- Associate of the Casualty Actuarial Society (ACAS) - in progress
- SOA Exam P, FM, IFM, STAM passed
What Does a Actuarial Analyst Do?
- Design, develop, and maintain software solutions using R, Python, SQL and related technologies
- Collaborate with cross-functional teams including product managers, designers, and QA engineers to deliver features on schedule
- Write clean, well-tested code following industry best practices for actuarial analyst and loss reserving
- Participate in code reviews, technical discussions, and architecture decisions to improve system quality and team knowledge
- Troubleshoot production issues, optimize performance, and ensure system reliability across all environments
Resume Tips for Actuarial Analysts
Do
- Quantify impact with specific numbers - team size, users served, performance gains
- List R, Python, SQL prominently if they match the job description
- Show progression - more responsibility and scope in recent roles
Avoid
- Vague phrases like "responsible for" or "helped with" without specifics
- Listing every technology you have ever touched - focus on what is relevant
- Including outdated skills that are no longer industry standard
Frequently Asked Questions
How long should a Actuarial Analyst resume be?
One page is ideal for most Actuarial Analyst roles with under 10 years of experience. If you have 10+ years, major leadership scope, publications, or highly technical project history, two pages can work as long as every section is relevant.
What skills should I highlight on my Actuarial Analyst resume?
Prioritize skills that appear in the job description and match your real experience. For Actuarial Analyst roles, R, Python, SQL, Excel/VBA are strong starting points, but the final list should reflect the specific posting.
How do I tailor my resume for each Actuarial Analyst application?
Compare the job description with your summary, skills, and most recent bullets. Add exact-match terms like actuarial analyst, loss reserving, pricing models, claims analysis, risk modeling where they are truthful, then reorder bullets so the most relevant achievements appear first.
What should I avoid on a Actuarial Analyst resume?
Avoid generic responsibilities, long paragraphs, outdated tools, and soft claims without evidence. Replace phrases like "responsible for" with action verbs and measurable outcomes.
Should I include projects on a Actuarial Analyst resume?
Include projects when they prove relevant skills or fill gaps in work experience. Strong projects show the problem, your role, the tools used, and the result. Skip personal projects that do not relate to the job.
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