We analyzed 915 entry-level actuarial job postings to find the most in-demand technical skills. Here's exactly what employers are looking for — ranked by frequency.
What Skills Do You Actually Need for an Entry-Level Actuarial Job?
If you're preparing to land your first actuarial role, you've probably wondered which skills to prioritize — should you learn Python or R? Does Excel still matter? How many exams do you really need before applying?
We analyzed 915 entry-level and intern actuarial job postings from our database to answer these questions with data. Every insight in this article comes directly from real job descriptions, parsed and categorized by our AI analysis engine.
Here's what we found.
The #1 Technical Skill: Excel (60% of All Entry-Level Jobs)
Before we get to programming languages and actuarial methods, there's one tool that towers above everything else: Microsoft Excel.
Excel appears in 60.0% of entry-level actuarial job postings — more than double the next most-requested tool. For context, Python (the most popular programming language) is mentioned in just 23.2% of postings.
This is a pattern that surprises many candidates who assume the industry has fully moved on to code-first workflows. It hasn't — at least not at the entry level. Excel proficiency is still a baseline expectation across pricing, reserving, and reporting functions.
Top tools mentioned in entry-level actuarial jobs:
| Tool | Jobs | % of Postings |
|---|---|---|
| Excel | 549 | 60.0% |
| PowerPoint | 313 | 34.2% |
| Microsoft Access | 76 | 8.3% |
| Power BI | 74 | 8.1% |
| Tableau | 43 | 4.7% |
| Git / GitHub | 14 | 1.5% |
| Jupyter Notebook | 11 | 1.2% |
| Databricks | 8 | 0.9% |
| Snowflake | 8 | 0.9% |
PowerPoint appearing in 34% of postings is also worth noting — communication and presentation skills are baked into the job even at the entry level.
Programming Languages: SQL Edges Out Python
Among coding languages specifically, SQL leads the pack at 26.3% of postings, narrowly ahead of Python at 23.2%.
Programming languages in entry-level actuarial jobs:
| Language | Jobs | % of Postings |
|---|---|---|
| SQL | 241 | 26.3% |
| Python | 212 | 23.2% |
| R | 157 | 17.2% |
| VBA | 104 | 11.4% |
| SAS | 97 | 10.6% |
| C++ | 23 | 2.5% |
| C# | 19 | 2.1% |
| Java | 10 | 1.1% |
| MATLAB | 5 | 0.5% |
| JavaScript | 5 | 0.5% |
Why SQL Outranks Python at the Entry Level
The SQL lead reflects the reality of early-career actuarial work: a large portion of entry-level tasks involve pulling, cleaning, and manipulating data from relational databases — experience studies, claim extracts, policy data. Python comes in just behind, driven by the surge in predictive modelling and data science adjacent roles.
The Surprising VBA and SAS Numbers
VBA (11.4%) and SAS (10.6%) rank 4th and 5th — and here's something interesting: both are proportionally more common at entry level than at senior level.
- VBA: 11.4% (entry) vs 8.7% (senior)
- SAS: 10.6% (entry) vs 7.5% (senior)
This suggests that many of the more process-oriented, legacy-system roles — particularly in life insurance and pension — tend to hire junior talent. If you know SAS or VBA, don't assume it's obsolete; a meaningful slice of the market still runs on it.
Entry vs. Senior: The Python Gap
Comparing entry vs senior levels across languages reveals that Python demand is higher at senior roles (27.5% vs 23.2%). The gap is modest but consistent. Entry-level candidates who invest in Python are positioning themselves well for career progression, not just for getting their first job.
Actuarial Methods: Predictive Modelling and Experience Studies Dominate
When it comes to actuarial methods specifically requested in job postings, two stand out well ahead of the rest:
Actuarial methods in entry-level job postings:
| Method | Jobs | % of Postings |
|---|---|---|
| Predictive Modelling | 180 | 19.7% |
| Experience Studies | 171 | 18.7% |
| Cash Flow Testing | 81 | 8.9% |
| Reserve Variability Analysis | 64 | 7.0% |
| Frequency / Severity Modelling | 49 | 5.4% |
| Time Series Forecasting | 40 | 4.4% |
| Asset-Liability Modelling | 34 | 3.7% |
| Stochastic Reserving | 32 | 3.5% |
| Life Contingencies | 32 | 3.5% |
| Chain Ladder | 30 | 3.3% |
| Reinsurance Pricing | 27 | 3.0% |
| Scenario / Stress Testing | 24 | 2.6% |
| Catastrophe Modelling | 21 | 2.3% |
| Machine Learning Models | 19 | 2.1% |
| Economic Capital Modelling | 18 | 2.0% |
Predictive modelling appearing in nearly 1-in-5 entry-level postings signals how much the industry has shifted. Employers aren't just looking for students who can read a loss triangle — they want people who can build and interpret models.
Experience studies (18.7%) reflect the enduring importance of mortality, lapse, and morbidity assumption work — particularly in life and health insurance.
Cash flow testing (8.9%) is notable for appearing this frequently at entry level, traditionally a task associated with more senior valuation actuaries.
Where Are Entry-Level Actuaries Actually Working?
The actuarial function data shows which teams are most actively hiring at the junior level:
| Function | Job Count |
|---|---|
| Business Intelligence & Reporting | 267 |
| Pricing & Rating | 246 |
| Reserving & Valuation | 226 |
| Predictive Modelling / ML | 165 |
| Underwriting Support | 99 |
| Regulatory Reporting (IFRS/GAAP) | 95 |
| Data Engineering & Pipelines | 94 |
| Product Development | 83 |
| Experience Studies & Assumptions | 66 |
| ALM | 38 |
| Risk Management / ERM | 31 |
BI/Reporting, Pricing, and Reserving make up the top three — these three functions alone account for a substantial majority of entry-level openings. If you're targeting your first role, understanding data pipelines and reporting infrastructure is arguably as important as knowing classical actuarial methods.
Actuarial Software: Lower Bar Than You Might Expect
Specific actuarial software (AXIS, Prophet, PolySystems, RMS) has relatively low representation at entry level:
| Software | Jobs | % of Postings |
|---|---|---|
| AXIS | 14 | 1.5% |
| PolySystems | 8 | 0.9% |
| Prophet | 3 | 0.3% |
| RMS | 3 | 0.3% |
7.4% of postings reference generic actuarial software without naming a specific platform. The takeaway: employers largely don't expect entry-level candidates to already know proprietary modeling systems. These are tools you learn on the job.
Do You Need Exams Before Applying?
One of the most common questions from actuarial students: how many exams do I need to get my first job?
The data gives a clear answer:
| Min Exams Required | Jobs | % of Postings |
|---|---|---|
| Not specified | 748 | 81.7% |
| 1 exam | 134 | 14.6% |
| 2 exams | 28 | 3.1% |
| 3+ exams | 2 | 0.2% |
| 0 (explicitly stated) | 3 | 0.3% |
81.7% of entry-level postings don't specify a minimum exam requirement. Among those that do, 1 passed exam is the most common ask (14.6%).
This doesn't mean exams don't matter — having passed Exam P or FM demonstrates commitment and quantitative ability. But the data suggests that many employers are willing to hire based on potential and then support exam progress from there.
Study Support: A Hidden Factor in Employer Selection
Of the postings that explicitly mention study support, 97% offer it (121 jobs out of 125 with a clear answer). Only 4 postings explicitly state no study support is offered.
This is a meaningful perk to look for when evaluating offers. The 86% of postings that don't mention it either way are worth asking about directly in interviews.
Degree Requirements
A degree is essentially expected:
- 75.3% of entry-level postings require a degree
- 12.1% prefer but don't require one
- Only 1.5% explicitly state no degree requirement
Relevant majors for actuarial roles typically include mathematics, statistics, actuarial science, computer science, economics, and finance.
The Lines of Business Hiring Most at Entry Level
Among jobs with a specified line of business:
| Line of Business | Job Count |
|---|---|
| Individual Life / Protection | 73 |
| Commercial / Employer Health | 58 |
| Health (Other) | 54 |
| Individual Annuities | 53 |
| Multi-Line | 52 |
| Pension (DB) | 50 |
| Commercial Property | 32 |
| Personal Property / Homeowners | 29 |
| Reinsurance (P&C) | 27 |
| Workers' Comp | 25 |
| Personal Auto | 23 |
Life, health, and pension collectively dominate entry-level hiring. Property & casualty roles are present but represent a smaller share of junior openings.
The Entry-Level Actuarial Skills Checklist
Based on this analysis, here's a prioritized skills checklist for anyone targeting their first actuarial role:
Must-have (mentioned in 20%+ of postings):
- Excel (advanced: pivot tables, VLOOKUP, array formulas)
- PowerPoint / data presentation
- SQL (data querying, joins, aggregations)
- Python or R (data manipulation, basic modelling)
High-value additions (10–20% of postings):
- Power BI or another BI tool
- VBA (especially for life/pension-focused roles)
- SAS (particularly at legacy-system employers)
- Predictive modelling fundamentals
- Experience studies methodology
Good-to-have (5–10% of postings):
- Tableau
- Cash flow testing concepts
- Frequency/severity modelling
- At least 1 passed actuarial exam (P or FM)
Key Takeaways
- Excel is still essential. 60% of entry-level roles ask for it — more than any coding language.
- SQL beats Python at entry level, though Python is growing and closes the gap at senior levels.
- Predictive modelling is mainstream, not niche — nearly 1 in 5 entry-level postings reference it.
- Exams are not a hard gate. Most postings don't require any. One exam is the most common explicit ask.
- Specific actuarial software (AXIS, Prophet) is rarely required — it's learned on the job.
- VBA and SAS are more common at entry level than senior level — don't discount them.
- Business intelligence, pricing, and reserving are the three functions doing the most junior hiring.
This analysis is based on 915 entry-level and intern actuarial job postings on Acturhire, analyzed using our AI job intelligence engine. Data reflects postings as of March 2025.