It's March already! Before we know it, a quarter of 2018 will be history. And it brings high school (and college!) seniors a little closer to graduation!

I've gotten a few emails over the last couple of weeks asking for advice on whether an actuarial career or career in data analytics would be a better career path/better course of study. My short answer, and probably an answer no one wants to hear - you can't go wrong with either. My detailed answer is below if you keep reading!

Before making this decision, it is so important to understand yourself. What is your passion as it relates to a future career? What type of projects do you enjoy working on? Are you a very disciplined person? What factors motivate and drive you?

Well, guess what? If you like problem solving and critical thinking - you can't go wrong with either! Similarly, if you like coding and learning how to develop solutions using code, again, either choice would be great! Problem solving and critical thinking is part of the day-to-day job responsibilities whether you are an analytics professional or actuarial professional and there is quite a bit of overlap in the technical skills you'll need to have.

If taking exams isn't your strong suit, it might be worth reconsidering the actuarial career path. Exams are a HUGE part of being an actuary. They say you have to study 100 hours for each hour of the exam. So that's easily at least 300 hours per exam minimum (more in my personal experience). Are you going to have the discipline to follow a rigid study schedule in order to get through 10 exams (assuming the FCAS track)? If you end up failing an exam, will you be able to continue to stay motivated in order to pass the next exams?

If having letters after your name from an established, world renowned organization is important to you, then following the actuarial career path may be a good fit for you. This also helps set you apart from many other non-credentialed professionals. I do have to say, the feeling of seeing that "PASS" message on my three CBT exams was probably one of the best feelings I've ever had. To work so hard to achieve something and get the results you're looking for is incredible. 

A career in analytics will allow you to do similar work as an actuary, without the added stress of all of the studying. Sure, you won't get nice bonuses and raises for each exam you pass, but if you start your career at a great company and do well, you should be just as fine. Following a career in analytics may also be good if you enjoy variety in the work you do and don't want to limit yourself to a specific industry. In many cases, as an actuary you will mainly be working in the insurance industry - there are some positions out there outside of insurance, but they aren't as common. If you want to be doing cool analytics or models for a big name, like Google, Coca Cola, Netflix, or NBC, analytics would be the way to go. 

(Shoutout to my favorite student loan paying app, Giving, use code SB346381 to join!)
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Student loans won't pay themselves.. isn't that the truth?!? Between student loans and the cost of living in some major cities, it's understandable why salary would also be a key component of this decision. I just grabbed a quick comparison from glassdoor below, but I highly encourage you to do your own research based on some of the entry level positions you're seeing in your area. You may also want to throw data scientist into the mix if that's the path you're looking to pursue. 

In my opinion, I wouldn't be too concerned with the salaries (or job security for that matter) for either analytics or actuarial roles since they're pretty similar. I definitely wouldn't allow that to be a deciding factor in your career choice, but it is something to be aware of as you are choosing your line of work. Given the nature of actuarial and analytics work, there will continue to be a demand over the coming years. If you're worried about future job security, then I would be careful to choose a solid company and become an expert in your field sooner rather than later.

If you keep going back and forth between pursuing an actuarial career or a career in analytics, my advice would be to start with the actuarial career path for a couple of reasons. 

This may not be true for everyone, but the longer you are out of school/university, the more you lose in terms of your study habits and routines, making it more difficult to get back into the swing of things. If you start studying (and passing!) actuarial exams during college, you'll be off to a really great start and have a solid foundation as you continue through the exam track as you're working full-time.

I've always had so many positive things to say to career changers interested in pursuing an actuarial career later on in their life, but the truth is it is HARD. It's definitely possible and there are a lot of successful career changers who have gotten great jobs in the field, but it's much easier to secure a role earlier on in your career. 

To pursue a career in analytics after trying out the actuarial path will be a lot easier since there are so many analytics careers out there and a lot of the work you do as an actuary - especially coding in Python, SAS, R, etc. - will be 100% relevant to many analytics jobs out there. It will always be more challenging to flip from analytics to actuarial due to the large number of qualified actuarial candidates at the earlier stages of the career.  

If you're an actuary, you probably love data. Or studying. Or days off for studying. Or some of the above. And whether you love data or not, you work with it daily and most likely perform analyses or create models. As technology becomes smarter and faster, companies are finding more ways to track information and collect data. This influx of additional data is great for building models and testing assumptions, but can at times make other analyses more complex and complicated. 

Excel is an actuary's best friend, but sometimes even excel can't handle the data if there's too much of it (I used to get the "not enough memory" error way too many times)! There are also quite a few limitations if you are only using excel to review and analyze your data. Based on my experience:

• Pivot Tables and Conditional Formatting are okay for reviewing data, but you can't compare multiple dimensions at once. 
• Filtering and flagging data only goes so far - in many cases you are still scrolling through data reviewing other attributes. 
• You don't get a good overview of your data in excel - it's important to know your population and it's not easy to get an all encompassing overview.  

So let’s talk about data visualization. Sure, data visualization may not be necessary in some cases, but I hope by the end of this post, if you’re someone who thinks “why visualize data when I can easily perform my analysis in excel” that you may have more of an interest on how data visualization can enhance your work. Or better yet, maybe you'll get inspired and develop a proof of concept to show your boss in order to bring in a data visualization tool! Keep reading for five examples of how data visualization can enhance your work as an actuary!

No matter what type of work you do as an actuary, there may be times where you will need to review data quality to make sure the data is expected. Or maybe you need to check the outcome of a model to see what the data looks like. Typically, a lot of this review is done in excel and results in scrolling through rows and rows of data or analyzing pivot tables. There's only so much you can see in a table - this is why when you're reviewing loss development triangles, it's usually best to use the red/yellow/green conditional formatting. Using a visualization tool, such as Tableau or Power BI can help you quickly draw insights and identify the data points you should focus on.

Example: Suppose you need to review claim amounts and premium amounts for a specific period for personal auto policies. Maybe you also care about the deductible amount and age of the policyholders. You'd most likely use a pivot table to review this information, but you could miss the big picture. If you use a visualization tool, you'd be able to plot a scatterplot with claim amount and premium amount on the axis, with each point's size based on the deductible amount and color based on age or an age bucket.

One of the main reasons I love visualizing data is because of the versatility of reviewing multiple dimensions of data at once. It can save a lot of time and help you focus on the most important information!

If you're exploring attributes affecting a pricing or reserving model or doing data quality on specific sets of data, it may be more efficient to use data visualizations to being your review process so you know which characteristics of the data to focus on. 

Example: You may be in a situation where you need to analyze claims for a specific line of business and find patterns for specific attributes of data. Are there specific zip codes that are typically reporting more damage on vehicles? Could the age or number of drivers on a policy be impacting this uptick? A visualization tool can help you explore multiple characteristics on one dashboard so you can see how they interact with one another. Once you know which characteristics you want to focus on, you can finalize your dashboard and any time you have new data you want to review, it's just a quick upload with minimal set-up. 

Data visualizations allow for a lot of versatility when it comes to comparing data, especially year over year comparisons. If you're doing data quality, you may have one set threshold for all of the data when it may make more sense looking at different thresholds for each state. This would add a lot more time to a review in excel, but using data visualization, these thresholds, when used with filters, would make the process more efficient and accurate.

It's also really easy to add in new calculations in Tableau or Power BI once the source data has been added - so if you're in the middle of creating a dashboard and want to see a new combination of data or bucket the data, you can easily do so in the visualization software.

Example: There may be a time where you need to compare data year over year to make sure different groupings of data remain consistent. Maybe you are looking at the loss ratio or a variety of other ratios. Depending on your dataset, there are a variety of ways you could visualize year over year data to compare, from bar charts to scatterplots to heatmaps. You could even use side by side box and whisker plots to see how the population of data has changed year over year.

​When using data visualizations to filter and compare data, the possibilities are endless, as well as the insights that can be drawn from the data. Data visualizations can also make your comparisons and data checks more effective! Just another reason I think data visualization is a great alternative!

There may be some situations where you want to see what your data looks like without certain subsets of data. There isn't an easy way to do this in excel. You could create a VBA macro that could exclude certain records with a click of a button, but why go through all of that trouble when you could do the same thing using visualization software and get a better overview of how different metrics change when excluding data?

Example: If you are interested in how specific lines of business are trending over time and you want to identify and exclude outliers causing large shifts, you could easily do this using visualization tools. With all of the additional features in tableau, you can also have visuals interact where you'd be able to hover over a bar in one chart which could highlight all of the data making up that specific bar in a different chart. 

Depending on the work you do, you may find a lot of relationships in your data which you must use to make assumptions, create models or test for data quality. There may also be processes in place for you to adequately review these relationships. However, when done the right way, data visualizations and interactions between visuals can show you additional information in seconds that may take hours to find in excel. Interactive dashboards can also help you get to the problem areas of your data and see the makeup of those problem areas with quick drill-down features. 

Example: When reviewing certain relationships, such as a loss ratio, you may see that a specific state stands out and you want to drill down to find the line of business causing the high loss ratio. You also want to see if it is one policy driving the loss ratio or many and if they have any other similar characteristics. In excel, you might be able to set specific thresholds and filter on these thresholds to find that data, but you could be missing some other important information. Maybe there is an issue with a specific product across the board, but you only found one point of data above the set threshold, so you let it go. Using a dashboard with multiple visualizations, allowing you to drill-down to the data could quickly alert you to these patterns without missing any specifics due to set thresholds.

I've found the drill-down capabilities of Tableau and Power BI to be very useful in identifying specific areas of data to focus on. It is a lot quicker to find these data points using a variety of visuals than it is to find these relationships in excel. 

I have experience using both Tableau and Microsoft Power BI, but there are also plenty of other data visualization tools out there, too. Check out the articles below for more information!

​If you are interested in applying data visualizations to your actuarial work, I'd be happy to speak more  - just send me a message on LinkedIn use the contact form on this site!

Related Articles:
The 38 Best Tools for Data Visualization 
Tableau vs Power BI: Comparing Pros and Cons

When it came to getting ready to apply for a full-time job, NYU Stern had me covered. During my time at school, I had the opportunity to attend countless resume workshops and had my resume reviewed by multiple professors. I learned the importance of having a dynamic resume during freshman year and I've spent countless hours modifying the content and format of my own resume. I'm hoping this post can help anyone looking for an entry-level actuarial job and give some great tips to enhance resumes to help them stand out.

I've seen TONS of resumes and it's easy to tell how much time someone has spent on their resume by looking at the format. I've seen numerous college graduates use the same format I used to get a job at a movie theater when I was 16 (it took me about 15 minutes to type up my first resume). You should spend as much time on the format of your resume as the content (A LOT more than just 15 minutes). A resume represents you; you want to show you've put time into creating it. The following tips should help create an eye-catching resume that will make HR recruiters pause and give your resume the time it deserves.

Separate Sections.  You should be able to look at your resume and in an instant be able to gather key information (where you went to school, which exams you've passed, past employers, technical skills, etc.). You cannot do this without distinct sections. My favorite way to separate sections (education, actuarial exams, job experience, etc.) is using a horizontal rule.

Spacing.  Feel free to play around with spacing. If you feel like you do not have enough room on your resume (it should be no longer than a page), even after changing the font size to 9 and changing the margins, try to change the spacing between each section. Maybe you want a bigger space between the main sections (work experience, education, etc.) and a smaller space between the other sections (jobs, clubs/activities, etc.).

Bold/Italicize.  Use bolded or italicized text to help break down your resume further and draw attention to specific areas within your resume.

Indentations.  Play around with indentations to help differentiate titles from text. Bullet points for text also helps!

Order.  Order your resume in a way that will help employers find what they are looking for. The order will change throughout your career, but when you are starting off and looking for your first job out of school, I would make sure education is at the top, followed by actuarial exams and work experience.

Consistency.  Everything on your resume should be consistent. If you bold titles in one section, you need to make sure to bold them in another. The same goes for any other formatting changes. It's easy to spot inconsistencies in formatting and it may show an employer you are careless. 

Lastly, I recommend Googling 'resume formats'. Using a cookie cutter template off the internet isn't the greatest idea since other people may have the same thought, but take a look at other resumes to get ideas for what you like and don't like. You may like how one resume separates the main sections, but you may like how another lays out the text under each section. Make your resume your own and build off of what you like from other resumes!

Formatting your resume is the fun part; coming up with what you are going to put in your resume is the hard part. Here are some tips to help you get that call for an interview.

Action Verbs.  Try to begin each bullet of text with an action verb. 

Applicable Skills.  Maybe you have no actuarial (or insurance) experience. If that's the case, think of everything you've done in your past positions and try to shape them into something applicable to actuarial work. Maybe you worked at a fast food restaurant during college. Did you try to improve processes? Did you work well with customers? Anything can be applicable to a resume for an actuarial position, you just may have to dig a little deeper to find those relatable skills. 

Numbers.  If you want to be an actuary and work with numbers the rest of your life, you should try to show that in your resume by being focused on quantitative measurements. Think of everything you've done in your past roles and try to quantify what you can. Maybe you taught classes or tutored students. How many did you teach/tutor? How many sessions?

Keywords.  After doing some research on the actuarial industry, you should have a good idea of what employers are looking for. Cater your resume to common job requirements. Maybe they want someone with great communication skills - try to use keywords that show that. For example, a good keyword may be 'collaboration'. 

Differentiate Yourself.  Everyone applying for these positions most likely majored in math or actuarial science, passed an exam or two and has at least some programming skills. What makes you different? What would make you add value beyond the day to day grind of work? Maybe you're really passionate about animals and volunteer a lot. Add that to your resume! If you don't think it fits, maybe try to make a new section in your resume for volunteer experience. It helps to show you're a human and have interests outside of studying all the time. 

Limit Past Experience.  No need to keep your high school on your resume for your first full-time job. For entry-level, I would take off anything over 5 years old unless there is something that will really 'wow' a prospective employer.

Actuarial Exams.  Make sure to include these on your resume! No need to include the scores, just a pass is fine. They have their own section on my resume, but I think including actuarial exams with relevant skills could also be a great way to present this on a resume. Don't forget the date passed!

Proofread.  Make sure to proofread your resume after making any significant changes. Actuarial work requires precision and accuracy - all it takes is missing a comma or zero to potentially make a big mistake. If a prospective employer notices an error on your resume, no matter how small, it could go in the trash immediately. Have someone else go through your resume, too, to make sure everything makes sense.

The main thing to keep in mind while you're thinking of what to put in your resume is how a prospective employer might react after reading it. If you think they will read it and it won't matter, either take it out or change it to better suit what you are trying to convey. Everything you write in your resume should have a purpose. You shouldn't just add information because you feel like it needs to be there, you should add it because it will help your chances of getting a call for an interview. 

Moral of the story, you're allowed to struggle on the first exams. That doesn't mean you're not good enough to be an actuary. It means you're still learning how to study and prepare for these difficult exams. Part of the process is figuring out how best to study and how to use your study time wisely. If I chose to get through the entire manual before MFE, I wouldn't have passed. Thanks to failed attempts on other exams, I knew to switch my focus from the manual to practice problems to be better prepared for exam day. 

I can't say I love taking exams or love studying, but I can say that passing an actuarial exam is a really great feeling. Best of luck on future exams!

Most recent exam struggle: two cats who insist on using my study manuals as beds.