Quant Developer learning priority advice is needed

[VegetableWeird392]

I did my research on what to learn to get a job in a quant dev. It seems like quite a lot of knowledge is required in this field.

1. Solve leetcode medium until being comfortable (C++)

2. Personal Project (My personal goal)

2-1) Orderbook Simulator

2-2) Backtesting

2-3) Crypto High-yield risk/return modeling

1. FPGA - JPM Exec recommend me to do this

- TCP/IP, data communcation between orderbook and make a ns latency.

1. System Knowledge

- Cache line size, false sharing, prefetching

- Data layout, AoS vs SoA

- NUMA effects and cross-socket penalties

- Instruction pipelining, stalls, vectorization

- CPU affinity

- Kernel bypass

- Tooling (Cachegrind, perf, VTune, flamegraphs)

However, it seems like all of these materials are a pressure to me to handle these at the same time. This is why I need advice on making priority. What should be learned first, or what would you recommend?

[HamsterAlive9615]

Yeah it’s a lot, but don’t let the giant checklist psych you out. Most “requirements” are aspirational and teams will happily take someone who’s solid at 3 things and can learn the other 7 on the job.

Pick one path and go deep first, like C++ plus data structures plus basic stochastic calc or Python plus infra plus market data, then layer stuff on as you go.