Statistician
Designs studies and uses math to find reliable patterns and answers in data.
Market pay — 79,210–170,700 USD/yr.
People who love math, are careful with evidence, and like drawing solid conclusions from numbers.
A day in the life
Plans how to collect data, builds statistical models, runs analyzes, checks that the results hold up, and explains what they mean.
Who it fits
People who love math, are careful with evidence, and like drawing solid conclusions from numbers.
Try it in a week
- Watch 2–3 “a day in the life of a Statistician” videos to see the real day-to-day, not the job-post version. ↗
- Take a free intro course to find out whether the topic clicks before you spend money or time on it. ↗
- Find someone doing it on LinkedIn or an industry group and ask 5 pointed questions: the daily grind, the money, and how they got in.
- Reproduce a simple experiment or analysis from a video and write up what you saw and what surprised you. That's research in miniature. ↗
How to get there
- Aug Build your college list and start your essays (summer before senior year)
- Oct FAFSA opens (typically Oct 1) - apply for federal financial aid
- Nov Early Action / Early Decision deadlines (many schools)
- Jan Regular Decision deadlines (often Jan 1-15)
- Mar Admission decisions arrive (mid-March to early April)
- May National College Decision Day - commit and pay your deposit
Approximate pathways. Requirements and test policies vary by state and school - always verify on the college's or program's official site.
Frequently asked
How much does a Statistician earn?
79,210–170,700 USD/yr — BLS. This is the middle band of the market: a beginner usually sits closer to the lower end, an experienced specialist closer to the top. A lot also depends on where you are. ~30k jobs in the US (BLS OEWS, May 2024)
How do you become a Statistician?
Most often through these fields: Statistics. See specific programs and requirements in the “How to get there” section below.
Who is this profession a good fit for?
People who love math, are careful with evidence, and like drawing solid conclusions from numbers.