Build strong math skills: calculus, linear algebra, probability, statistics
Learn programming: Python, SQL, and one low-latency language like C++ or Java
Study financial markets, instruments, and trading basics
Learn time series analysis, stochastic processes, and optimization
Practice data analysis and model building on real datasets
Master machine learning fundamentals and model validation
Develop strong problem-solving and mental math skills
Learn risk management and portfolio construction
Read quant finance books, research papers, and market microstructure material
Work on projects involving backtesting and strategy research
Gain experience with data cleaning, feature engineering, and signal testing
Improve communication skills for explaining models and results
Pursue relevant education in math, physics, computer science, engineering, or finance
Apply for internships or entry-level roles in trading, research, or data science
Build a portfolio of projects and code samples
Prepare for technical interviews in probability, statistics, coding, and brainteasers
Stay current with market developments, tools, and research
Network with quants, traders, and researchers in the industry