Summary of "college majors that DO and DON’T make money"
Business / revenue-focused summary of majors
The video frames college major choices primarily through economic outcomes (starting salary, ROI, lifetime earnings) plus practical constraints (difficulty, hours, additional training).
High-earning / “does make money” majors (and implied business logic)
Engineering
- Why it pays: High demand for technical problem-solving roles.
- Key metrics stated:
- Median starting salary: ~$74,000
- Projected starting salary range: ~$66,000
- Subfield example:
- Higher: nuclear engineering (higher earnings mentioned)
- Lower (but still high): biomed engineering
- Tradeoff / operations constraint: “engineering is brutal,” implying heavy workload and lower work-life balance during school.
Computer Science (CS)
- Why it pays: Still high demand despite fears about market disruption/automation.
- Key metrics stated:
- Average starting salary: ~$77,000
- Risk noted (high level):
- CS job market is “cooked”
- AI may replace software engineers eventually, but “not anytime soon” (per speaker)
- Actionable career “playbook” (tips to get employable):
- Prepare for lots of math (more than just coding; includes proofs)
- Work on side projects (build tangible artifacts: app/portfolio/game)
- Embrace basic professionalism (“shower” joke used to break stereotype)
Healthcare
- Why it pays: Clinical roles have strong compensation; AI/tech integration increases long-run demand.
- Key metrics stated:
- Nursing starting salary: ~$65,000
- Physician assistant starting salary: ~$104,000
- “Hundreds of thousands by mid-career isn’t uncommon” (no exact CAGR/figures given)
- Tradeoff: Brutal hours + long training pipeline (MCAT → medical school → residency → etc.).
IT / Information Technology
- Why it pays: Practical demand as companies shift to cloud and modern infrastructure.
- Key metrics stated:
- “Salaries into the six figures” for cloud specialists (no precise number)
- Operations / entry barrier claim:
- Lower barrier than many high-paying fields
- May not require a bachelor’s degree (associates/certs suggested)
- Concrete example given:
- Speaker “hired one a few months ago” (cloud specialist demand claim)
- Role taxonomy (market map):
- System administrators
- Network engineers
- IT project managers
- Cyber security analysts
- Cloud specialists
Finance (shown as high ROI, but high intensity)
- Why it pays: Strong compensation + fast progression in certain sub-industries.
- Key metrics stated:
- Average ROI on a bachelor’s in finance: 1,842%
- Average starting salary: ~$85K
- Expected lifetime earnings: ~$9.7 million
- Tradeoff / workload: “brutal hours”
- Concrete workplace policy example:
- September 2024: JP Morgan implemented an 80-hour weekly cap on junior investment bankers
- Career progression example (investment banking):
- Analyst: $85–$100K
- Associate (2–3 years): $150–$225K
- Vice President (after 3–4 more years): $300K–$550K
- Further progression to Director (total comp “into the seven figures”)
- Skills note: Quant analyst roles require very strong math (IMO-level mentioned), but many finance roles rely more on applied stats/modeling than heavy STEM.
Lower-paying / “doesn’t make as much money” majors (and how to mitigate)
Fine Arts
- Key metrics stated:
- Average starting salary: ~$49,000
- Benchmark: average bachelor’s degree ~$55,000
- Mitigation strategy (career alignment):
- Degree doesn’t determine pay—role does
- Example pivot: fine arts → marketing/communications (better outcomes than “staying purely arts”)
Education (explicitly framed as poor ROI)
- Key metrics stated:
- Negative lifetime ROI: -555.43%
- “149K to be exact” (presented as the scale of loss; wording implies net cost/outcome)
- Primary school teaching starting salary: ~$41,000
- Higher-paying alternative roles (no numbers given):
- Technical writer
- HR specialist
- Corporate trainer
- Constraint: genuine love required; pay is described as insufficient.
Humanities (lower starting salaries, but transferable skills)
- Key metrics stated (examples):
- History starting salary: ~$49,000 (~11% below average college grads)
- Business-relevant transferable skills emphasized:
- English → writing/communication → marketing, communications, social media
- History → research/analysis → business analytics
- Philosophy → critical thinking → tech/law/finance/consulting
- Actionable recommendation (initiative required):
- Don’t passively assume the degree limits you—choose career mapping intentionally
- Example framing: balance money vs passion (marketing vs corporate vs finance depending on fit)
Social sciences / Psychology (lower ROI unless you add grad school)
- Key metrics stated:
- Bachelor’s starting salary: ~$50–60K
- Clinical psychologist (with doctorate) median annual salary: ~$96K
- Mitigation paths:
- Use psychology skills in industry (selling ideas, managing teams, communications)
- Alternative “monetization route” mentioned: content creation (humor/example)
Theology
- Key metrics stated:
- Average starting salary: ~$42,000
- Mitigation strategy:
- If financial stability matters: roles in educational institutions, clinics, nonprofits
Execution-focused frameworks / playbooks embedded in the talk
The video doesn’t formalize OKRs/SWOT, but it repeatedly applies an informal decision framework:
- Earnings feasibility framework: compare starting salary, then consider lifetime earnings/ROI
-
Constraint tradeoff model: high pay is paired with workload/difficulty (engineering brutality; healthcare training; finance brutal hours)
-
Role-mapping strategy: degree → transferable skills → target role/industry (e.g., fine arts → marketing; humanities → communication/analytics/critical thinking; psychology → comms/team management)
-
Employability playbook (for CS):
- Math readiness
- Build side-project portfolio
- Demonstrate professionalism/basic readiness
Notable sponsorship / product mention (non-business)
- Opera (browser) mentioned as a sponsor, positioned as improving research workflow via:
- tab grouping, split-screen reading
- sidebar streaming player
- AI assistant (“Arya”) for Q&A and visual explanation
- Not directly tied to major selection economics.
Presenters / sources
- Presenter: Not explicitly named in the subtitles (solo speaker).
- Sponsor: Opera (mentioned as “the sponsor of today’s video”).
- Named external organization: JP Morgan (cited for an 80-hour weekly cap example, September 2024).
- Other cited “source” types (no direct links provided):
- A study reporting education degree negative lifetime ROI of -555.43% and “149K” figure.
Category
Business
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