compare careers
two careers. side by side. no hand-waving.
the question students actually ask is 'should i do x or y?' — pick two from the 23 careers, see the trade-offs that matter.
tech
Data Scientist
turn messy data into business decisions
business
Product Manager
decide what gets built and why
at a glance
the numeric + categorical fields. easy to scan side-by-side.
ai threat
medium · 45/100
low · 20/100
demand
very-high
high
stream
Science / Commerce / Any
Any
budget
low
medium
math intensity
4 / 5
2 / 5
degree vs skill
35% degree
55% degree
salary trajectory
₹ LPA, sourced — see provenance comments in /src/data/careers.ts.
fresher
₹6–10 LPA
₹8–15 LPA (APM; IT services ₹8–12L, product cos ₹15–25L — Glassdoor 892 reports cluster ₹11–22L P25–P75)
3 yr
₹12–22 LPA
₹20–35 LPA
7 yr
₹25–40 LPA
₹40–70 LPA
senior
₹50 LPA – ₹1.2 Cr
₹65 LPA – ₹3 Cr+ (VP / CPO)
how to get in
the 'which is more reachable for me' answer — buried inside two detail pages otherwise.
eligibility
Any degree. CS/Stats/Math helps but isn't required. Non-CS folks routinely transition in via projects + portfolio.
MBA helps for senior tracks. APM programs accept engineers / designers / analysts with strong product thinking. No specific degree required.
budget route
Free YouTube (Krish Naik, StatQuest) + Kaggle + 1 ₹500 SQL course + GitHub projects. ~6 months disciplined.
Build and ship 1 side product. Write 6 product teardowns. Apply to APM programs cold.
premium route
Scaler/Masai bootcamp or IIIT-B PG Diploma (~₹2–3L). Faster, mentored, placement-assisted.
Top MBA → APM. Or engineering at a product company → internal switch.
tools
- —Python
- —SQL
- —Pandas
- —scikit-learn
- —Git
- —Tableau / Power BI
- —dbt
- —Airflow (later)
- —Notion / Linear / Jira
- —Figma (read-only)
- —SQL (basic)
- —Amplitude / Mixpanel
- —Loom
certs that matter
- —Google Data Analytics (entry signal)
- —AWS Certified ML — Specialty (mid-level)
- —None reliably. Reputation > certs.
portfolio proof
- —3–4 end-to-end projects on GitHub with cleaned READMEs
- —1 Kaggle notebook with a real writeup
- —1 dashboard deployed publicly (Streamlit / Tableau Public)
- —Product teardowns on a blog/LinkedIn
- —Side product shipped to real users
- —Internship at a real product company
backups
- —Data Analyst
- —Analytics Engineer
- —ML Engineer
- —Business Analyst
- —Business Analyst
- —Strategy / Consulting
- —Growth Marketing
- —Founder's Office
the prose stuff
long-form fields don't compress into a table — expand to read. toggling a section opens it on both cards.
data scientist
product manager
full profile
Data Scientist
full profile
Product Manager