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Data Science & Analytics
Turn messy data into decisions.
Entry earning
$70k
Data Analyst
Senior tier earning
$220k
Lead / ML Scientist
Source: U.S. Bureau of Labor Statistics, Occupational Outlook Handbook
Words with a dotted underline are industry terms. Hover or tap for a plain-English definition.
What the job actually looks like
Data scientists pull large amounts of data from company systems, find patterns in it, and use those patterns to answer business questions or train AI models. Mostly writing code (Python/SQL) and making charts.
Paths inside the field
Pick a branch to retrace the arc
Click any specialization. The timeline and salary curve above update to match.
The full arc
How this career unfolds
Data Analyst
Data Scientist
Senior Data Scientist
Lead / ML Scientist
Surprising fact
A $3,000 Coursera specialization and a strong GitHub often beat a $60,000 master's for your first job.
Lifestyle & optionality
The day-to-day reality
Typical hours
40 to 50/wk
High
Very high
Very high
Very high
Where this is heading
10-year outlook
Projected job growth (2023 to 2033)
Source: U.S. Bureau of Labor Statistics
AI and automation risk
The job will exist but look fundamentally different in 10 years.
Tailwinds
- ML/AI talent in extreme demand
- Every company hiring data infrastructure
Headwinds
- Basic dashboarding/SQL work being absorbed by AI copilots
- 'Data scientist' title splintering into narrower roles
Real wages vs. inflation
Real wages up strongly, especially in ML engineering.
Routes in
Education paths & payback
Multiple real paths into this career, each with different odds, costs, and risks.
Smart start
Funded CS / stats
Top-20 program. Tuition waived + ~$40k . The single highest-ceiling path for ML research roles.
Placement reality
Frontier labs (OpenAI, Anthropic, DeepMind) hire researchers at $300 to $500k+ all-in. Quant funds (Two Sigma, Renaissance, Citadel) recruit PhDs at similar levels. Long path but near-zero financial cost.
Total cost
$0
Length
10 yrs
How we calculate it: total education cost ÷ (15% of first-year pay put toward paying it back).
Smart start
Public university CS / stats / math degree + portfolio
The realistic smart path. State school CS / stats / applied math degree + 1 to 3 strong personal projects on GitHub.
Placement reality
Most data analyst / data scientist roles at non- companies hire from any 4-year degree if you can demonstrate skills. Salary $70 to $100k start at most companies.
Total cost
$55k
Length
4 yrs
How we calculate it: total education cost ÷ (15% of first-year pay put toward paying it back).
Standard route
Bootcamp / online cert + portfolio (no degree)
Springboard, Metis, DataCamp + Kaggle competitions. Works for entry-level data analyst roles, especially if you're switching careers from another field.
Placement reality
Mid-size companies will hire bootcamp grads at $60 to $80k for analyst roles. and quant funds rarely hire bootcamp grads directly without a degree.
Total cost
$12k
Length
1 yrs
How we calculate it: total education cost ÷ (15% of first-year pay put toward paying it back).
Standard route
Top CS / stats master's at MIT, Stanford, CMU, Berkeley
Required-ish for ML researcher / scientist roles at and AI labs. Overkill for most data analyst / data scientist work.
Placement reality
Highest-leverage credential for ML scientist seats at OpenAI, Anthropic, DeepMind, Google Research. Worth the cost only if research is your goal.
Total cost
$260k
Length
6 yrs
How we calculate it: total education cost ÷ (15% of first-year pay put toward paying it back).
The real cost will be different for you
The numbers above are medians from the U.S. Bureau of Labor Statistics. The price you actually pay depends on financial aid, scholarships, family help, state residency, and which schools accept you. A "$250k" private university is often $60k to $120k after aid. A "cheap" community college can still be out of reach without a plan. Use these as a starting point, then get real quotes from the specific schools you're considering.
Location matters
How pay changes by metro
Pay differs by about 20-35% across the country. Cost of living often cancels most of it.
| Metro | Pay at Senior Data Scientist |
|---|---|
San Francisco Bay Area, CA | $216k |
New York City, NY | $208k |
Seattle, WA | $195k |
Boston, MA | $189k |
Washington, DC | $187k |
Los Angeles, CA | $184k |
Denver, CO | $170k |
Chicago, IL | $166k |
Austin, TX | $165k |
Atlanta, GA | $157k |
Dallas–Fort Worth, TX | $155k |
Phoenix, AZ | $150k |
Nashville, TN | $147k |
Indianapolis, IN | $141k |
Rural / small metro | $125k |
How to read this: Pay is US median for Senior Data Scientist scaled by BLS metro wage data. Cost of living index is C2ER (US avg = 100). A means that metro isn't just paid better. It's essentially required to work at the top of this field.
Start now
What you can do in high school
Classes & electives
- AP Computer Science
- Calculus
- Statistics
- Physics
Things to try outside class
- Build something, even a small website, app, or script
- Try free courses on freeCodeCamp, CS50, or Khan Academy
- Join robotics, coding club, or a hackathon
- Contribute to an open-source project on GitHub
Read, listen, watch
The cheapest way to find out whether you actually like a field is to read what people in it read.
- 'The Pragmatic Programmer' by Hunt & Thomas (habits of good engineers)
- 'Soul of a New Machine' by Tracy Kidder (how computers actually get built)
- Hacker News daily (news.ycombinator.com) and Lenny's Newsletter
- The Changelog and Lex Fridman podcasts
None of this is required. It's just the lowest-friction way to find out if you actually like this kind of work before you commit money or time.
Salary and progression source: U.S. Bureau of Labor Statistics, Occupational Outlook Handbook (bls.gov/ooh). Figures are medians or typical ranges in today's dollars; real outcomes vary by employer, city, and specialty.