Some resouces for getting started with data science and quant. 

Statistics & Regression: 

• Wooldridge - Introductory Econometrics 
• Hastie - Elements of Statistical Learning 
• Shumway - Time Series Analysis and Its Applications 
• Yamane - Statistics for Economists, Courses 
• Lambert - A graduate course in econometrics 
• Cunningham - Causal Inference: The Mixtape 
• Taboga - Statlect
• Soch - Book of Statistical Proofs
• Mudders are invited to join Harvey Mudd Data Science

Linear Algebra & Optimization

• Peter - Mathematics for Machine Learning 
• Boyd - Convex Optimization
• Axler - Linear Algebra Done Right
• Petersen - Matrix Cookbook
• Bishop - Numerical Methods: Linear Algebra
• LibreTexts - Assorted resouces

Deeper Models

• Russell - Artificial Intelligence: A Modern Approach 
• Silver - DeepMind x UCL | Introduction to Reinforcement Learning 
• AWS - MLU-Explain 
• Murphy - Probabalistic Machine Learning 

Competitive Programming

• Laaksonen - Competitive Programmer’s Handbook
• Qi - USACO Guide
• Kogler - Algorithms for Competitive Programming
• Problem Banks: CodeForces, AtCoder, Project Euler, Kattis, CodinGame, Grind75

Brainteaser Collections: 

• Zhou - A Practical Guide To Quantitative Finance Interviews
• Crack - Heard on The Street
• Mosteller - Fifty Challenging Problems in Probability
• Winkler - Mathematical Puzzles, Mathematical Mind-Benders
• Mathai - An Introduction to Geometrical Probability
• Gardner - The Colossal Book of Short Puzzles and Problems
• Bogomolny - Cut the Knot
• Lehoczky - The Art of Problem Solving

Fun Reads: 

• Dama - On Automated Trading
• AoPS - Broken Stick variations
• Wildenhain - Microsoft Word is Turing Complete
• Murphy - GradIEEEnt Half Decent
• Marx - Calculus