DeskPrep
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Quant · Trading · Trading Operations

Practise the work, not just the questions.

DeskPrep turns finance interview prep into work simulation. Downloadable Python, Excel, SQL, Linux and C++ tasks, plus questions, cases and mark schemes, built around the quant, trading and operations desks you are interviewing for.

View packs and pricingSee how it works

One-time purchase · no subscription · download and keep every task

3
role tracks
5
file formats
100%
tasks with mark schemes
£0
recurring one-time only

role tracks

Pick your track

Each pack is a self-contained library of exercises and mark schemes for one hiring track buy only what maps to your interviews.

[QR]£49

Quant Research & Quant Trading

Probability, derivatives and signal work in the exact file formats quant desks hand out.

  • Probability & Statistics
  • Options & Derivatives
  • Volatility
  • Python Exercises
  • Market Microstructure
  • +4 more
.py.ipynb.sql.sh.cpp.xlsx
[TR]£49

Trading & Execution

Mental maths, market making and desk cases that mirror live trading assessments.

  • Mental Maths Drills
  • Market Making
  • Options Intuition
  • Risk/Reward Reasoning
  • Trading Desk Cases
  • +1 more
.xlsx.py
[TO]£39

Trading Operations & Middle Office

Trade lifecycle, reconciliations and blotter work as they appear in ops take-homes.

  • Trade Lifecycle
  • Excel Exercises
  • SQL Exercises
  • Python Exercises
  • Linux/Shell Exercises
  • +1 more
.xlsx.sql.py.sh

downloadable take-home tasks

Not a question bank. A desk simulation.

Most prep gives you questions and answers. DeskPrep gives you incomplete files and asks you to finish the work then shows you the model solution and the rubric it is marked against.

  • Starter files with deliberate gaps to complete
  • Mark schemes that explain the reasoning, not just the output
  • Worked solutions with common mistakes flagged
  • Role-matched tasks so every exercise is relevant
bs_pricer_starter.py
# DeskPrep complete the pricer
import numpy as np
from scipy.stats import norm

def bs_call(S, K, T, r, sigma):
    # TODO: compute d1, d2
    d1 = ___
    d2 = ___
    return (S * norm.cdf(d1) - K * np.exp(-r * T) * norm.cdf(d2))

# mark scheme unlocks after your attempt
████████████████████████████

how it works

Three steps, per exercise

01

Download the brief and starter file

Open a README written like a desk task: what you are given, what to deliver, and the constraints to apply.

02

Complete it as you would on the job

Work in the real format a spreadsheet, a Python script, a SQL query or a shell pipeline under a realistic time estimate.

03

Mark your work against the scheme

Compare against the model answer and points rubric. See the common mistakes and what separates a weak answer from a strong one.

exercise library

Real files, every format a desk uses

Download the starter file, work offline, then unlock the mark scheme and model solution. A representative sample below.

Python

Pricers, pandas tasks, backtests

Excel

Blotters, PnL, reconciliation

SQL

Trade, settlement, exposure queries

Linux / Shell

Log parsing, file processing

C++

Pricing skeletons, data structures

EXCELbeginner

Trade Blotter Completion

Complete booking fields side, quantity, price, fees and status then flag rows that fail validation.

Trading Operations~30 min
PYTHONbeginner

Black-Scholes Pricer

Finish a European option pricer, derive d1/d2 and return the Greeks for a given parameter set.

Quant Research~40 min
EXCELintermediate

Daily PnL Attribution

Decompose desk PnL across price move, FX, fees and carry, and reconcile to the reported total.

Trading & Execution~60 min
SQLintermediate

Counterparty Exposure Query

Write a query set that aggregates net exposure by counterparty and surfaces limit breaches.

Trading Operations~45 min
PYTHONadvanced

Vol Surface Analysis

Clean a quotes file, build an implied-vol surface and comment on skew and term structure.

Quant Trading~90 min
LINUXintermediate

Failed Trades Log Parsing

Parse settlement logs with shell tooling to extract failed trades and summarise failure reasons.

Trading Operations~50 min

pricing

Simple, one-time pricing

Buy a single track from £39, or bundle for full coverage across quant, trading and operations. No subscriptions, ever.

pack

Quant Pack

Quant research & quant trading take-homes.

£49one-time

  • Probability, derivatives, volatility and microstructure tasks
  • Python, SQL, shell and C++ starter files
  • Full mark scheme for every exercise
pack

Trading Pack

Trading & execution desk assessments.

£49one-time

  • Mental maths and market-making drills
  • Excel and Python desk cases
  • Full mark scheme for every exercise
pack

Trading Ops Pack

Trade lifecycle & middle office tasks.

£39one-time

  • Trade lifecycle and reconciliation exercises
  • Excel, SQL, Python and shell starter files
  • Full mark scheme for every exercise
best value
bundle

Quant + Trading Bundle

Both desk tracks for candidates hedging quant and trading.

£89one-time

  • Everything in the Quant Pack
  • Everything in the Trading Pack
  • Save £9 versus buying separately
bundle

All Three Bundle

Every track the full DeskPrep library.

£119one-time

  • All three packs included
  • Quant, trading and operations coverage
  • Save £18 versus buying separately
Compare all packs

faq

Frequently asked questions

Is this a question bank or a subscription?

Neither. DeskPrep sells downloadable take-home exercises with mark schemes. Every purchase is a one-time payment with no recurring billing.

What file formats do the exercises use?

Tasks come in the formats desks actually use: Python (.py and .ipynb), Excel (.xlsx), SQL (.sql), shell scripts (.sh) and C++ (.cpp), depending on the track.

Who are the packs for?

Candidates preparing for quant research and quant trading roles, execution and market-making trading roles, and trading operations or middle office roles.

Do I need to buy everything?

No. Buy a single track for £39-£49, or save with the Quant + Trading bundle (£89) or the all-three bundle (£119).