SIG / Susquehanna quant interview preparation: a role-specific study guide

Prepare expected value, conditional decisions and implementation reasoning for a Susquehanna application. The firm’s trading page describes game theory and quantitative modelling in its training; individual vacancies give role-specific criteria. The original examples below connect those ideas to practice. They are not leaked questions, an employer-endorsed guide or a universal description of SIG interviews.

Separate trading, research and technology

Susquehanna's trading careers page describes traders working with researchers and technologists, and training that uses game theory and quantitative modelling. That supports studying those subjects, but it does not establish a fixed interview question list. Use the current vacancy for the office and stream you intend to join.

A London quantitative strategy developer vacancy describes coding, mathematics, systems design and behavioural interviews for that particular graduate role. It is a useful example of why “SIG interview” is too broad a preparation category. Do not infer that every trading or operations applicant follows the same process.

Decision practice: compare the action with the alternative

An expected-value calculation should describe what happens if you act and what happens if you decline. Include entry costs and the possibility that a counterparty chooses when to participate. In a game, an opponent's action can be evidence about private information. Start with simple conditional models before trying to read a complex strategy from a small sample of outcomes.

Explain a choice under uncertainty

Practise stating a fair value, a risk limit and the observation that would make you change your mind. A positive expected payoff need not justify an arbitrarily large position. Discuss the downside distribution and what you would learn after settlement. This makes your reasoning inspectable even when the eventual outcome is random.

Implementation practice

For a technology or strategy-development application, build a small replay of actions and resulting positions. Test that a buy increases inventory, that cash reflects the trade price and that a repeated event is handled according to a specified rule. Then explain the design to someone who did not write it. Follow the vacancy and recruiter instructions when selecting languages and interview format.

Original practice questions with worked answers

1. A net expected payoff

A game costs 4 to enter. A fair die pays 12 on a 6 and 3 on any other result. What is the expected net payoff?

Answer. Gross expectation is 12/6 + 5×3/6 = 4.5. Subtract the entry fee to obtain 0.5. Positive expected net value is distinct from a guaranteed gain.

2. Optional reroll

A fair die pays its face value. You may keep the first roll or replace it with one final independent roll. What is the optimal rule and expected payout?

Answer. A replacement has mean 3.5, so reroll 1, 2 or 3 and keep 4, 5 or 6. Expected payout is (3×3.5 + 4 + 5 + 6)/6 = 4.25. You cannot keep the better of both after choosing to reroll.

3. Ties and equity

In a heads-up game you win 35% and tie 20% of deals. What is your share of a pot that splits equally on ties?

Answer. Equity is 0.35 + 0.5×0.20 = 0.45, or 45%. Outright win probability is only 35%; the remaining 45% are losses. Betting costs and folds are outside this setup.

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Primary sources and scope

Employer information was checked on the review date. Our study activities and original questions are editorial suggestions. Recruiting requirements, regional processes and vacancies can change; the employer’s current instructions take priority.