Top 12 Insurance Analyst Skills to Put on Your Resume

Applying for an insurance analyst role means proving you can wrangle data, judge risk, and translate numbers into decisions. Hard skills matter. So do judgment, context, and clarity. Signal both—cleanly—so a hiring manager can spot them in seconds.

1. Risk Assessment

Risk assessment is the structured evaluation of how likely losses are and how severe they could be—across people, property, events, or portfolios—to set coverage terms, limits, and pricing that reflect reality.

Why It's Important

It anchors pricing and capital decisions. Done well, it reduces volatility, improves loss ratios, and protects both insurer and insured when the unexpected barges in.

How to Improve Risk Assessment Skills

Sharpen the inputs and the thinking.

Leverage modern analytics: Use predictive models and scenario testing to quantify frequency and severity more precisely.
Elevate data quality: Standardize sources, clean anomalies, and document lineage so models aren’t guessing.
Track regulatory change: Map rule shifts to rating plans and assumptions before they go stale.
Study emerging risks: Climate, cyber, litigation trends—build them into forward-looking views.
Collaborate deeply: Sit with underwriters, actuaries, claims, and fraud teams to stress-test assumptions with ground truth.

How to Display Risk Assessment Skills on Your Resume

2. Data Analysis

Data analysis for insurance turns raw policy, exposure, and claims data into insight: cleaning, joining, modeling, and interpreting patterns to guide underwriting, pricing, retention, and reserving.

Why It's Important

It reveals loss drivers, uncovers fraud signals, informs segmentation, and spots trends early—so decisions move from gut feel to measurable impact.

How to Improve Data Analysis Skills

Strengthen statistics: Distributions, hypothesis testing, time series, GLMs—core tools for insurance data.
Go beyond basics in Excel and SQL: Build robust queries, audit trails, and pivot-heavy summaries that stand up to scrutiny.
Adopt scripting tools: Use R or Python for reproducible workflows and advanced models.
Visualize clearly: Tell the story with clean charts and dashboards that highlight action, not noise.
Build domain context: Understand coverage forms, claim lifecycles, and regulatory nuances to interpret outputs correctly.
Practice on real datasets: End-to-end projects—data intake to recommendations—cement skill.

How to Display Data Analysis Skills on Your Resume

3. SAS

SAS is a suite for data management, statistics, and reporting. In insurance, it powers ratemaking studies, pricing models, and operational reports at production scale.

Why It's Important

Many carriers run core analytics and reporting in SAS. Proficiency lets you handle large datasets, apply rigorous methods, and deploy trusted outputs into business workflows.

How to Improve SAS Skills

Nail the fundamentals: DATA/PROC steps, macros, and essential procedures.
Manipulate data efficiently: Master joins, merges, arrays, and PROC SQL for complex pipelines.
Level up modeling: Logistic/linear models, survival analysis, scorecards, and validation.
Polish reporting: Create repeatable, parameterized outputs; use visual analytics when needed.

Work with real workloads: Rebuild pricing or loss triangles in SAS to pressure-test performance.

Engage the community: Patterns, code snippets, and troubleshooting accelerate growth.

How to Display SAS Skills on Your Resume

4. SQL

SQL is the language of relational data. It retrieves, shapes, and aggregates the tables behind policies, exposures, billing, and claims.

Why It's Important

Insurance data sits in warehouses and operational systems. SQL gets you answers fast and reproducibly—no guesswork, no copy-paste chaos.

How to Improve SQL Skills

Master core patterns: Joins, window functions, CTEs, subqueries, and set operations.

Think in models: Understand schemas, keys, and normalization to query cleanly.

Tune performance: Index awareness, sargable predicates, and explain plans to cut runtimes.

Validate rigorously: Reconcile counts, use checksums, and test edge cases.

Automate: Schedule jobs and parameterize queries for repeat reporting.

Blend with BI: Feed Tableau or Power BI models with efficient, well-structured views.

How to Display SQL Skills on Your Resume

5. Excel

Excel is the quick-turn lab for insurance analytics: fast audits, sanity checks, prototypes, and crisp summaries.

Why It's Important

It’s universal. When you need to explain, reconcile, or prototype, Excel shortens the distance between data and decision.

How to Improve Excel Skills

Advanced formulas: XLOOKUP, INDEX(MATCH), SUMIFS, COUNTIFS, dynamic arrays.

Pivot mastery: Build interactive summaries with slicers, grouping, and custom calcs.

Clean visuals: Dynamic charts, minimal ink, clear labeling, and consistent scales.

Power Query + Power Pivot: Transform messy data and build robust data models.

Automation: Use macros/VBA sparingly to eliminate repetitive tasks safely.

Forecasting: Apply time-series tools and error checks to avoid overfitting.

How to Display Excel Skills on Your Resume

6. Tableau

Tableau turns insurance data into dashboards that people actually use—interactive, layered, and fast to grasp.

Why It's Important

Clarity changes behavior. With the right visuals, trends, anomalies, and outliers jump out, guiding action instead of debate.

How to Improve Tableau Skills

Get the basics tight: Data connections, tidy data, and chart selection.

Prep data well: Clean, reshape, and document your steps for repeatability.

Design for decisions: Emphasize comparisons, highlight thresholds, and surface KPIs.

Add analytics: Reference lines, cohorts, parameters, and forecasting when appropriate.

Optimize performance: Extracts, fewer quick filters, and efficient calculations.

Iterate with users: Short feedback cycles beat perfect designs built in a vacuum.

How to Display Tableau Skills on Your Resume

7. Underwriting

Underwriting weighs applicant risk and sets terms, limits, and price—balancing growth with discipline.

Why It's Important

It’s the margin gatekeeper. Strong underwriting protects combined ratios and capital while keeping offers competitive.

How to Improve Underwriting Skills

Blend judgment with data: Use models to inform, not replace, expert review.

Standardize data intake: Better submissions, fewer unknowns, tighter risk selection.

Adopt predictive signals: Enrich with external data where allowed; test lift before rollout.

Refresh guidelines: Align appetite with loss experience and market conditions.

Speed the experience: Reduce friction for brokers and applicants without losing rigor.

How to Display Underwriting Skills on Your Resume

8. Actuarial Science

Actuarial science applies probability, statistics, and financial theory to price risk, build reserves, and keep insurers solvent.

Why It's Important

It’s the quantitative backbone for pricing and capital. Without it, rates drift, reserves wobble, and surprises get expensive.

How to Improve Actuarial Science Skills

Deepen math and stats: Loss distributions, credibility, survival analysis, stochastic modeling.

Use modern tools: R/Python for repeatable analyses, simulation, and diagnostics.

Study regulation and standards: Reporting rules and reserving guidelines change the calculus.

Pursue credentials: Formal exams sharpen rigor and signal expertise.

Bridge to finance: Understand discounting, capital costs, and reinsurance structures.

How to Display Actuarial Science Skills on Your Resume

9. Python

Python is the Swiss army knife for analysis and automation—fast data wrangling, strong modeling libraries, and clean pipelines.

Why It's Important

It handles large datasets, automates repetitive work, and enables predictive models that improve pricing, retention, and fraud detection.

How to Improve Python Skills

Own the data stack: Pandas, NumPy, and robust IO for reliable pipelines.

Visualize smartly: Matplotlib and Seaborn for clear, minimal, truthful charts.

Automate: Scripts that pull, clean, and publish recurring reports on a schedule.

Learn ML basics: Scikit-learn for classification, regression, and model validation.

Ship projects: End-to-end work—from raw data to decisions and documentation.

Write clean code: Modular functions, tests, and version control to keep changes safe.

How to Display Python Skills on Your Resume

10. R Programming

R excels at statistics, visualization, and reproducible analysis—ideal for pricing studies, reserving, and exploratory work.

Why It's Important

Powerful packages and a statistical-first mindset make R a natural fit for actuarial and analytical workflows.

How to Improve R Programming Skills

Solidify fundamentals: Data structures, functions, and idiomatic R.

Adopt the tidyverse: dplyr, tidyr, readr, and ggplot2 for clear pipelines and visuals.

Model with intent: GLMs, time series, and resampling with careful validation.

Use insurance packages: Tools for loss reserving and actuarial distributions.

Reproducibility: Quarto/R Markdown and projects with documented dependencies.

Community learning: Code reviews, discussions, and shared patterns accelerate progress.

How to Display R Programming Skills on Your Resume

11. Financial Modeling

Financial modeling translates business mechanics into numbers—forecasting premiums, losses, expenses, and capital impacts under different paths.

Why It's Important

It links portfolio performance to strategy. You can test scenarios, gauge sensitivity, and steer decisions with confidence.

How to Improve Financial Modeling Skills

Excel at structure: Clear inputs, transparent calcs, and labeled outputs with controls.

Use robust functions: INDEX/MATCH or XLOOKUP, dynamic arrays, and audit checks.

Model insurance specifics: Earned/uneared premium, loss development, expenses, and reinsurance.

Scenario and sensitivity: Best/base/worst, catastrophe shocks, rate changes, and mix shifts.

Bridge to code: Supplement with Python/R for simulations and large-scale analysis.

Document assumptions: Version control and clear notes prevent model drift.

How to Display Financial Modeling Skills on Your Resume

12. Power BI

Power BI is a data modeling and visualization platform that turns raw insurance data into governed, shareable dashboards.

Why It's Important

It centralizes metrics, standardizes definitions, and enables near-real-time monitoring across underwriting, claims, and distribution.

How to Improve Power BI Skills

Master DAX and Power Query: Calculations, relationships, and data transformations that scale.

Define insurance KPIs: Loss ratio, frequency, severity, retention, new business hit rate—make them consistent.

Use templates and themes: Standardize look, feel, and metric definitions across reports.

Explore advanced visuals: Decomposition trees, key influencers, and custom visuals when they add clarity.

Model for performance: Star schemas, incremental refresh, and efficient measures.

Practice on real data: Build dashboards that answer recurring business questions.

Iterate with stakeholders: Short cycles to refine usability and trust.

How to Display Power BI Skills on Your Resume