The world of actuarial science is changing fast, and if you’re aiming for a top internship in 2026, it’s no longer enough to just have a solid GPA and a few math classes under your belt. The competition is fierce, with companies like New York Life, MetLife, and CNO Financial Group seeking interns who not only understand probability and statistics but can also apply programming skills to real-world insurance problems[1][4][8]. Passing the Society of Actuaries (SOA) Exam P is a great start—it proves you’ve got the foundational probability knowledge—but what really sets you apart is how you combine that exam success with practical coding ability. Here’s how to leverage both to land (and excel in) a 2026 actuarial internship, with real examples, insider tips, and actionable steps you can start taking today.

Why Programming and Exam P Matter More Than Ever #

Actuarial work isn’t just about crunching numbers by hand anymore. Insurers are hungry for interns who can build models, automate reports, and analyze massive datasets—skills that require more than just Excel wizardry. In fact, MetLife’s internship description explicitly mentions that knowledge of Python, SQL, or R is preferred, and New York Life looks for candidates familiar with modeling packages and programming languages[1][4]. Meanwhile, passing Exam P signals to employers that you’ve mastered the probability concepts essential for pricing, reserving, and risk management.

But here’s the thing: plenty of applicants will have passed Exam P. Far fewer will be able to write a Python script that simulates claim frequencies or use SQL to pull policyholder data for a profitability analysis. That’s your opportunity. When you walk into an interview with a GitHub portfolio full of actuarial projects and a passed exam, you’re not just another candidate—you’re someone who can add value from day one.

Building a Standout Skillset: From Exam Prep to Code #

Let’s break down how to build this killer combination, step by step.

Master Exam P—But Don’t Stop There #

Start by acing SOA Exam P. This exam covers probability fundamentals: combinatorics, random variables, probability distributions, and expectation. These concepts are the bedrock of actuarial work, whether you’re pricing a new life insurance product or projecting future claims. Use reputable study materials, join a study group, and take plenty of practice exams. Aim not just to pass, but to truly understand the material—interviewers can tell the difference between rote memorization and real comprehension.

Once you’ve passed, don’t let the momentum fade. Start thinking about how these probability concepts show up in real actuarial tasks. For example, how would you model the probability of a policyholder lapsing? Or estimate the expected number of claims in a given period? These are the kinds of questions you might face in an internship interview, and they’re much easier to answer if you’ve internalized the exam material.

Learn to Code—Start Simple, Build Fast #

You don’t need to be a software engineer, but you do need to be comfortable with at least one programming language. Python is the most versatile choice for actuaries—it’s easy to learn, has fantastic libraries for data analysis (like pandas and numpy), and is widely used in the industry. SQL is also essential for querying databases, and R is still popular in some actuarial circles.

Start with online tutorials or a community college course. Once you’re comfortable with the basics, challenge yourself with actuarial-specific projects. For example, write a Python script that simulates a portfolio of life insurance policies, calculates the probability of ruin, and visualizes the results. Or use SQL to extract policyholder data and calculate lapse rates by demographic. These projects don’t have to be perfect—what matters is that you’re applying your coding skills to actuarial problems.

Combine Both Skills in Real Projects #

This is where you really separate yourself from the pack. Take the probability concepts from Exam P and use your programming skills to build something tangible. Here are a few project ideas:

• Claim Frequency Simulator: Use Python to simulate claim frequencies for an auto insurance portfolio, applying the Poisson and negative binomial distributions you learned in Exam P. Visualize the results with matplotlib or seaborn.
• Reserving Calculator: Build a tool in R or Python that estimates claim reserves using basic chain ladder techniques, then compare your results to those produced by actuarial software.
• Pricing Model: Create a simple premium calculator for a term life product, factoring in mortality rates, expenses, and profit margins. Add a user interface with Streamlit or Shiny for bonus points.

Upload these projects to GitHub and mention them in your resume and cover letter. When interviewers ask about your technical skills, you’ll have concrete examples to share—something most other candidates won’t.

Crafting an Application That Gets Noticed #

With your skills in place, it’s time to put together an application that stands out. Here’s how to make every piece count.

Resume: Show, Don’t Just Tell #

List Exam P under your education or certifications section, but don’t stop there. Create a “Projects” section where you describe the coding projects you’ve completed, with links to your GitHub. Use bullet points that emphasize the actuarial relevance of each project, like “Built a Python simulation of auto insurance claim frequencies using Poisson distribution” or “Developed a SQL query to analyze policyholder lapse rates by age band.”

If you’ve had any relevant work experience—even a part-time job in data entry or a student research assistant role—highlight the technical and analytical aspects. Did you use Excel to track inventory? That’s a start, but if you automated a report with VBA or Python, say so.

Cover Letter: Tell Your Story #

Your cover letter is your chance to connect the dots between Exam P, your programming skills, and your passion for actuarial science. Don’t just repeat your resume—explain why you’re excited about the intersection of math, coding, and insurance. Mention a specific project that sparked your interest, or talk about how you used programming to solve a problem in a class or internship.

Personalize each letter for the company you’re applying to. If you’re applying to New York Life, reference their focus on product development and risk management[1]. For MetLife, highlight your interest in pricing and reserving, and mention any experience with actuarial modeling[4]. This shows you’ve done your homework and aren’t sending generic applications.

LinkedIn and Online Presence #

Make sure your LinkedIn profile is up to date, with a clear headline like “Actuarial Science Student | Exam P Passed | Python & SQL.” Add your projects to the “Featured” section, and consider writing a short post about one of them—this can catch the eye of recruiters. Follow companies you’re interested in and engage with their content. Sometimes, a well-timed comment or message can lead to an informational interview.

Acing the Interview: Technical and Behavioral Prep #

If your application gets you in the door, the interview is your chance to shine. Here’s how to prepare for both the technical and behavioral sides.

Technical Questions #

Expect to be asked about probability concepts from Exam P, often in the context of a business problem. For example, you might be asked to estimate the probability that a new insurance product will be profitable, or to explain how you would model claim frequencies for a health insurance portfolio. Brush up on the key distributions (Poisson, binomial, normal, exponential) and be ready to explain them in plain language.

You’ll also likely face coding questions, especially if you’ve highlighted those skills. These could range from writing a simple Python function to calculate expected value, to debugging a SQL query. Practice coding under time pressure, and be prepared to walk through your thought process out loud. Interviewers care as much about how you approach problems as they do about getting the “right” answer.

Behavioral Questions #

Companies want interns who are curious, collaborative, and eager to learn. Be ready to talk about a time you solved a tough problem, worked in a team, or learned a new skill on your own. Use the STAR method (Situation, Task, Action, Result) to structure your answers. For example: “In my probability class, we had a group project to model lottery odds. I took the lead on building a Python simulation, which helped us visualize the results and present to the class. We got an A, and I learned how to communicate technical concepts to non-technical audiences.”

Case Studies and Presentations #

Some companies, like MetLife, include presentations as part of their internship program[4]. You might be asked to analyze a dataset, build a model, and present your findings to a panel. Practice explaining your work clearly and concisely, using visuals when appropriate. Record yourself and watch for filler words, unclear explanations, or overly technical jargon.

Making the Most of Your Internship #

Landing the internship is just the beginning. Here’s how to maximize your experience and turn it into a full-time offer.

Be Proactive and Curious #

Ask questions—lots of them. Seek out opportunities to work on different types of projects, whether it’s pricing, reserving, risk management, or data analysis. Volunteer for tasks that stretch your skills, even if they’re outside your comfort zone. The more you learn, the more valuable you become.

Build Relationships #

Take advantage of networking events, mentorship programs, and social activities. MetLife, for example, offers networking events and mentorship as part of its internship program[4]. Get to know people in different departments, not just actuarial. You never know where your next opportunity—or reference—will come from.

Document Your Work #

Keep a journal of what you do each day, the skills you use, and the problems you solve. This will help you update your resume and LinkedIn, and give you concrete examples to discuss in future interviews. If possible, get permission to include samples of your work in your portfolio (with any sensitive data removed).

Seek Feedback #

Ask your manager and mentor for regular feedback. What are you doing well? What could you improve? Use this input to grow throughout the summer. Companies like New York Life and CNO Financial Group often consider interns for full-time roles, so showing that you’re coachable and eager to improve can pay off when offers are decided[1][8].

The Bigger Picture: Trends and Stats #

The actuarial profession is evolving, and employers are looking for candidates who can keep up. According to the Bureau of Labor Statistics, employment of actuaries is projected to grow faster than average over the next decade, but competition for entry-level positions remains intense. Companies are increasingly relying on data science and automation, making programming skills more valuable than ever.

A survey by the Society of Actuaries found that over 60% of employers now list programming as a desired skill for entry-level actuaries, and that number is rising. Meanwhile, Exam P remains one of the most common first exams for candidates, with thousands sitting for it each year. By pairing exam success with coding ability, you’re positioning yourself for not just an internship, but a long, successful career.

Final Thoughts: Start Now, Stand Out Later #

The path to a 2026 actuarial internship starts today. Pass Exam P, but don’t stop there—learn to code, build real projects, and showcase your skills in every part of your application. Be curious, be proactive, and don’t be afraid to ask for help along the way. The best actuaries aren’t just good at math; they’re problem solvers, communicators, and lifelong learners. By combining programming skills with a deep understanding of probability, you’re not just preparing for an internship—you’re building the foundation for a standout career.