1️⃣ Question 1 — Necessary skills for a data scientist

• ❌ Client service skills

• ✅ Statistics and probability

• ❌ Higher mathematics such as calculus (helpful but not always required)

• ❌ Domain-specific knowledge (important but not universally required)

Explanation:
Statistics & probability are core foundations every data scientist must know.

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2️⃣ Question 2 — Characteristic function of data scientists

• ❌ Extract & organize data (data engineering)

• ❌ Make decisions (business stakeholders)

• ✅ Build ML/DL models for business decisions

• ❌ Gather raw data (data collection role)

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3️⃣ Question 3 — Percentage of global companies using data analytics

• ❌ 25%

• ❌ 49%

• ❌ 78%

• ✅ 82%

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4️⃣ Question 4 — Fields where data scientists work

• ✅ Many different fields

• ❌ Academia

• ❌ Technology

• ❌ Math & statistics

Explanation:
Data science is used across healthcare, finance, retail, transport, manufacturing, etc.

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5️⃣ Question 5 — Good source of portfolio content

• ❌ NDA-restricted work

• ✅ Freelance work

• ❌ Examples found online

• ❌ Unfinished projects

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6️⃣ Question 6 — How to decide skills for your portfolio

• ❌ Asking friends

• ✅ Reading job listings

• ❌ Using a template

• ❌ Including everything

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7️⃣ Question 7 — Advice for building a new project

• ❌ Use random ideas

• ❌ Avoid messy real-world datasets

• ❌ Avoid communities

• ✅ Use GitHub to host your projects

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8️⃣ Question 8 — Should hobbies/interests be included?

• ❌ Never

• ❌ Always

• ❌ Only if limited experience

• ✅ Some are okay to help employers know you better

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9️⃣ Question 9 — Largest part of resume

• ❌ Skill summary

• ❌ Contact information

• ❌ Education

• ✅ Work experience

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🔟 Question 10 — Making resume ATS-friendly

• ❌ Use specialized jargon

• ❌ Add alt-text

• ❌ Add image files

• ✅ Use and repeat relevant keywords

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🧾 Summary Table

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