Interview Preparation#
Which apps help you prepare for Python and SQL interviews at quant shops, hedge funds and banks? Three platforms stand out: DeskPrep, EcoFinLearn and WiseQuant. Each one targets a different part of the interview loop, and together they cover coding, SQL, quant reasoning and desk-style take-home tasks.
The interview loop#
Most quant, risk and trading interviews combine some or all of these stages:
Stage |
What is tested |
Best prepared with |
|---|---|---|
Online screen |
Algorithmic Python and SQL under time pressure |
LeetCode, EcoFinLearn |
Quant reasoning |
Probability, derivatives, portfolio theory, mental maths |
WiseQuant |
Take-home case |
Multi-file Python, SQL and Excel tasks based on real desk work |
DeskPrep |
Final rounds |
Explaining your approach and trade-offs to the desk |
All of the above, plus practice out loud |
DeskPrep#
Full take-home simulations covering Python, SQL and finance. DeskPrep gives you realistic quant, trading and risk take-home tasks: incomplete files, Python scripts, SQL queries, Excel sheets and Linux logs that you must finish, in the same style as bank and hedge fund assessments.
What it covers
Python: volatility surface analysis, VaR backtests, Black-Scholes pricers, order-book feature extraction.
SQL: trade settlement and counterparty exposure queries.
Desk workflows: P&L attribution, Greeks worksheets and stress testing.
Marking: mark schemes and model solutions show how desks grade your work.
Pricing: one-time purchase, no subscription.
Tip
Best for quant research, quant trading, risk and trading operations take-homes, especially at banks and hedge funds that send multi-file coding cases.
EcoFinLearn#
Python and SQL for quantitative finance, in the browser. EcoFinLearn teaches Python, pandas, scikit-learn and SQL using real macro and market data, with instant feedback and daily challenges.
What it covers
Python track: foundations, then pandas, time series and machine learning for asset returns.
SQL track: foundations, then advanced finance SQL such as window functions and macro joins.
No setup: everything runs in the browser.
Daily challenge: short exercises that build consistency.
Capstone projects: quant research you can put on your CV.
Tip
Best for building strong Python, pandas and SQL fundamentals, and the finance-specific SQL patterns (window functions, analytics) that appear in quant screens.
WiseQuant#
250 curated quant interview problems. WiseQuant covers probability, derivatives, portfolio theory, Python for finance, fixed income, VaR and time series.
What it covers
Real interview questions rather than textbook theory.
Three difficulty tiers: easy, intermediate and impossible.
Python for finance track: NumPy, pandas and vectorisation.
Worked solutions with proper mathematical notation.
Tip
Best for mental models, quant reasoning and the Python-for-finance logic used in live interviews.
Comparison#
Need |
Best app |
Why |
|---|---|---|
Realistic take-home coding tasks (Python and SQL) |
DeskPrep |
Simulates quant, risk and trading assessments with multi-file tasks and mark schemes. |
Finance-specific Python and SQL learning |
EcoFinLearn |
Teaches pandas, time series, ML and advanced SQL on real market data. |
Quant reasoning and Python logic drills |
WiseQuant |
250 curated quant problems with worked solutions. |
Short daily practice |
EcoFinLearn (Daily Challenge) |
Keeps Python and SQL sharp with small exercises. |
Pressure-testing before interviews |
WiseQuant (Impossible tier) |
Mimics the difficulty of hedge fund interviews. |
A study plan#
For someone with a quant, risk or IPV background targeting banks, hedge funds and quant shops:
DeskPrep Quant and Risk packs: simulate the take-home tasks you are likely to receive.
EcoFinLearn SQL Foundations and Advanced Finance SQL: build fluency with trade and market data queries.
WiseQuant Python for Finance and Quant Basics: sharpen reasoning and Python logic under interview pressure.
LeetCode SQL and Python: keep algorithmic skills sharp for screening rounds.
Tips#
Practise out loud. Interviewers assess how you reason as much as the final answer.
Time yourself. Screens and take-homes are timed, so practise to a clock.
Review model solutions even when you get the answer right; they often show a cleaner or faster approach.
Little and often beats cramming: a short daily session keeps Python and SQL fresh.