Row 80556

Row ID: 80556 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 80556 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

**Should I self-study data science or work towards actuarial exams?**

I’m graduating from a Big 10 school in a few weeks as a math/statistics major. I didn’t have good enough grades to get into my schools MS stats program and was too late to apply to others. So I’ve been working towards taking the SOA actuarial exams instead. However, as I’ve been studying for these exams, I’ve realized how much I enjoy learning applied math and statistics concepts on my own. It’s making wish I could take graduate-level courses in statistics and making me reconsider the actuarial route.

Unfortunately, most stats-related jobs usually require a graduate degree (that was why I was drawn to the actuarial exams since you just need to pass the exams to demonstrate proficiency in a topic and can do that on your own). And I don’t have the technical skills needed for a data analyst job since my degree was more theoretical.

But I’m wondering if the time I’ll be spending studying for the actuarial exams (which is a lot; about ~200 hours/exam on the lower end, and there’s multiple exams) in the upcoming months could instead be used to bridge the gap in my skillset for data analyst roles. Meaning I could easily become proficient in the skills needed for an entry-level position in a *fraction* of the time needed for the actuarial exams, and hopefully land a job, then reapply to an MS Stats program for next year. Besides, I hear graduate degrees are becoming increasingly valuable for actuarial roles in recent years.

The only downside is that actuarial exams have a well-defined structure so you know exactly what you need to study and how to apply those topics, and there’s lots of resources on it. Plus, it’s a very linear career path. And each exam serves as a proof that you understand the relevant topics. It’s difficult to prove this when self-studying stats/data science (outside of a GitHub, I suppose). I don’t see any online certificate programs that seem worth it, except maybe the one Google has (please let me know if there’s others worth looking into)!

I’d appreciate any input on this!

FieldValue
text **Should I self-study data science or work towards actuarial exams?** I’m graduating from a Big 10 school in a few weeks as a math/statistics major. I didn’t have good enough grades to get into my schools MS stats program and was too late to apply to others. So I’ve been working towards taking the SOA actuarial exams instead. However, as I’ve been studying for these exams, I’ve realized how much I enjoy learning applied math and statistics concepts on my own. It’s making wish I could take gradu…
label r/datascience
dataType comment
communityName r/datascience
datetime 2024-05-24
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Raw Record

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  "text": "**Should I self-study data science or work towards actuarial exams?**\n\nI’m graduating from a Big 10 school in a few weeks as a math/statistics major. I didn’t have good enough grades to get into my schools MS stats program and was too late to apply to others. So I’ve been working towards taking the SOA actuarial exams instead. However, as I’ve been studying for these exams, I’ve realized how much I enjoy learning applied math and statistics concepts on my own. It’s making wish I could take graduate-level courses in statistics and making me reconsider the actuarial route. \n\nUnfortunately, most stats-related jobs usually require a graduate degree (that was why I was drawn to the actuarial exams since you just need to pass the exams to demonstrate proficiency in a topic and can do that on your own). And I don’t have the technical skills needed for a data analyst job since my degree was more theoretical. \n\nBut I’m wondering if the time I’ll be spending studying for the actuarial exams (which is a lot; about ~200 hours/exam on the lower end, and there’s multiple exams) in the upcoming months could instead be used to bridge the gap in my skillset for data analyst roles. Meaning I could easily become proficient in the skills needed for an entry-level position in a *fraction* of the time needed for the actuarial exams, and hopefully land a job, then reapply to an MS Stats program for next year. Besides, I hear graduate degrees are becoming increasingly valuable for actuarial roles in recent years. \n\nThe only downside is that actuarial exams have a well-defined structure so you know exactly what you need to study and how to apply those topics, and there’s lots of resources on it. Plus, it’s a very linear career path. And each exam serves as a proof that you understand the relevant topics. It’s difficult to prove this when self-studying stats/data science (outside of a GitHub, I suppose). I don’t see any online certificate programs that seem worth it, except maybe the one Google has (please let me know if there’s others worth looking into)!\n\nI’d appreciate any input on this!",
  "label": "r/datascience",
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  "datetime": "2024-05-24",
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