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The End of Biostatisticians?

The era of AI is upon us. Naturally, this means a lot of people are questioning whether their jobs will be automated by AI.

Biostatisticians are particularly worrisome when it comes to this matter.

This probably has something to do with our analytical, overthinking brains that makes us so inclined to this field in the first place.

Personally, I don’t think we need to be so worried.

Reasons Why Biostatisticians Are Safe

Here are some 10 reasons why I am not worried about AI taking biostatistician jobs, and you shouldn’t be either.

1. AI would be a threat to most jobs, not just biostatistics – If biostatisticians can be replaced – so can most other jobs, so at least we’ll all be unemployed. Adaptability is key in any field.

2. AI is a tool, not a replacement – I believe biostatisticians who integrate AI will be in demand. It will be used as a tool in your work, but it will not replace your need to use the tool.

3. We haven’t reached sentience (yet) – Human oversight in healthcare and statistics remains crucial. Until we have an iRobot situation, we shouldn’t be worrying so much – you’ll still need to oversee what AI is doing.

4. Healthcare and pharma are highly regulated industries – AI adoption is slower due to ethical, legal, and compliance concerns. The general public has a scepticism to “big pharma” as it is – try telling them that AI is in control.

5. AI-generated results will still require human expertise – AI can automate tasks, but statistical reasoning and validation are human-driven. Ask biostatisticians if chatGPT is even close to doing all their work now.

6. Pharmaceutical companies rely on regulatory approval – AI can’t yet handle FDA/EMA compliance, clinical trial design, or medical ethics alone. Regulatory bodies will not accept AI doing this work.

7. AI bias and errors make human verification essential – AI models can produce misleading results if not checked by experts. We’ve all had chatGPT make a mistake when you’ve asked it a question, bias and errors will happen.

8. Developing AI for biostatistics requires biostatisticians – AI models will depend on biostatisticians to develop, maintain and improve their functionality. Even if AI takes over, you will still be needed to maintain our AI overlords.

9. Public trust in AI-driven healthcare is low – Decision-making in medicine still requires human professionals to ensure accountability. Just like you wouldn’t fully trust chatGPT diagnosing you with a disease – trusting it to design studies and analyze complex data is fraught with doubt.

10. New AI-driven job roles will emerge – Biostatisticians who upskill in AI/ML will have opportunities in adjacent fields. Health data science and medical AI development will likely grow – this allows the savvy biostatistician to have some flexibility in the jobs they apply for.

Not convinced?

Look up recent job postings for biostatistician jobs. Notice that how there are still jobs available. Take a look at how many list AI/ML skills as requirements.

This is a great sign that the field is adapting to AI rather than being replaced by it, and it shows that there is still an ongoing demand for biostatisticians.

One interview after 3 months? Don’t worry! Keep your biostatistics resume as is. As you can see, by the end of the year you’ll be inundated with interviews…

The Harsh Truth About Biostatistics Resumes

It’s no secret that the biostatistics job market can be a tough one. If you’ve spent time on the r/biostatistics subreddit, you’ve probably seen job search Sankey diagrams that paint a harsh picture.

For example, one Reddit user applied to 300 jobs before landing a single job offer. In their words:

“TLDR; it’s rough out there folks.”

Or as another user, who applied for 330 jobs before they got a job offer, shared:

“I’ve been on the job hunt since early 2023 somewhat casually with some more serious portions of the search. I sent out a bunch of apps for jobs I probably wasn’t qualified for so that inflated the number, but it was brutal.”

Wow, that’s over a year and a half looking for a job!

The biggest hurdle in your job search? The application stage. In fact, over 90% of these applications are either ghosted or rejected*. This is an extremely high number when you consider how much time and effort you put into your job search, that is essentially, wasted.

(*93.65% based on the posts quoted above.)

So, how do you increase your chances of getting interviews? By reducing the amount of applications that get ghosted/rejected at this stage. Close this gap, then you stand a better chance at actually getting a job.

The good news is that it doesn’t have to be this hard. With the right tweaks, your resume can stand out from the pile.

I know this because I’ve done it. The last time I applied for jobs, I got multiple callbacks and landed a senior role, in a highly competitive remote position – plus a 37.8% salary increase.

A mistake a lot of biostatisticians make is to think their resume is just a summary of what you’ve done.

It’s not.

Your resume is a marketing document with one goal in mind – to get you interviews in a highly competitive field. And it needs to be written that way.

Is Your Resume Really a Problem?

You’ve applied to 30 jobs. Zero callbacks. Is your resume the problem? Probably.

A source suggest that you need to send around 10-15 resumes to get one callback. If you’re not hitting this callback rate, you probably need to start making some tweaks to your resume.

I know what you’re thinking, “I’ll just apply to more jobs and keep my current resume. Statistically speaking, I will get a interview eventually”.

I won’t argue with the stats but I will argue that this approach is a huge waste of your time and effort.

Instead, you can significantly increase your chances of getting an interview by just making one simple change to your resume!

Your Current Resume is Boring

Most biostatistics resumes read like job descriptions rather than success stories.

Here’s an example of a weak bullet point:

“Performed data analysis using R and SAS.”

I will say on behalf of everyone who has to read a resume like this, *yawn*.

This is vague, uninspiring and indistinguishable from every other resume. Hiring managers see hundreds like this.

This is a chance to sell yourself to the recruiter, not regurgitate your last job description or university project.

Fact is, a lot of applicant have the same background on paper when you look at them through this lens.

Every applicant has experience with programming and stats, has done the titanic survival analysis and has a degree.

This does not set you apart from other applicants and will not help you get that interview.

Your resume should sell you, not just list what you did.

The Anatomy of an Interview-Winning Biostatistics Resume

So how do you make your resume stand out from the rest? By transforming your experiences into quantitative, results-orientated actions.

Use this formula:

Action Verb + What You Did + Result (with Numbers)

For example:

Before: “Performed data analysis using R and SAS.”

After: “Analyzed clinical trial data using R and SAS, improving model predictive accuracy by 20%, leading to better patient outcome forecasts.”

Much better! The quantitative result makes it stand out.

You might ask, “What if I don’t have any clear, quantifiable outcomes?”. In that case, add a quantitative action instead.

For example:

Before: “Created statistical analysis plans based on study protocols.”

After: “Developed statistical analysis plans for five high-impact studies, aligning methodologies with trial protocols to enhance research validity.”

Even in academia or non-profits, results matter. All organizations need to save money or generate funding, and your work contributes to that. Showcase it.

Here’s an example:

Before: “Worked with a senior researcher on the analysis of progression time to Alzheimer’s Disease.”

After: “Collaborated with a senior researcher on the analysis of progression time to Alzheimer’s Disease by automating statistical processes to reduce the estimated analysis time from 4 weeks to 2 weeks.”

This highlights efficiency and impact – things every employer values.

Don’t have much work experience? No problem! Use examples of university projects, coursework and personal side-projects.

Why This Works

It shows not just what you did, but why it mattered.
Numbers grab attention. They’re easy to scan and prove real impact.
It differentiates you from other applicants. Your experiences are unique – your job description or university degree is not.

Try it Out For Yourself

Pick one bullet point from your current resume and rewrite it using the formula above. Describe the action you took. Show a quantitative result.

If you improved a process, how much faster did it get?
If you built a model, how accurate was it?
If you worked on a big client project, what was the value of it?

Simple.

Conclusion

That’s it – just one tweak. But it’s powerful. Apply this across your entire resume, and you won’t just “get through the system” – you’ll get noticed.

Most biostatistics resumes read like dry job descriptions. Don’t make the same mistake. Stand out, and land more interviews.

There’s more where that came from.

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