How do I break into data science without a math degree?

Senior DS who took the self-taught route checking in. You can absolutely break in without a math degree. I did it. **The reality of DS job postings:** - "PhD required" usually means "PhD preferred or equivalent experience" - Most DS work is 80% data cleaning, 20% actual modeling - Business understanding is undervalued by new grads but valued by employers - Your BA/analyst background is actually an asset **The realistic path (6-12 months of focused work):** **1. Core Python + SQL (Month 1-2)** - Python: pandas, numpy, matplotlib - SQL: Complex queries, window functions, joins - You probably know some SQL already **2. Statistics fundamentals (Month 2-3)** - You don't need a degree - Focus on: probability, distributions, hypothesis testing, regression - Khan Academy + Statistics courses on Coursera **3. Machine learning (Month 3-5)** - Start with scikit-learn - Understand: linear/logistic regression, trees, random forests, clustering - Andrew Ng's ML course (free) - Don't need to understand all the math, need to know when to apply what **4. Portfolio projects (Month 4-6)** - This is the most important part - 3-4 solid projects on GitHub - Use real datasets, solve real problems - Document your thinking **Your secret weapon:** You understand business. Most DS PhDs don't. You can: - Translate business problems to data problems - Communicate findings to non-technical stakeholders - Actually understand what matters This is more valuable than knowing advanced calculus. **Paths that work:** 1. **Internal transition** - Offer to help DS team, take on hybrid projects 2. **Analyst to DS pipeline** - Many companies hire "Data Analyst" roles that do DS work 3. **BI to DS** - Your analytics work counts **Do you need a Master's?** For FAANG/top-tier: Maybe helpful For 90% of DS jobs: Absolutely not Your experience + self-taught skills + portfolio = jobs paying $90-120k. Start learning today. Apply in 6 months. I went from $50k analyst to $110k DS in under 2 years.