Why pre-screen game theorists before the technical panel
Applied game theory fails on assumptions rather than on mathematics. Real players are not fully rational, do not know the payoff structure, and are not playing the game the model describes. A theorist who cannot say which assumptions their result depends on will hand a business a recommendation that is sound and inapplicable. A short screen tests both the formal command and the willingness to state what the model requires to hold.
What actually matters when screening Game Theorist candidates
- 01
Theoretical command
Probe command of equilibrium concepts and complexity: Nash versus correlated equilibria, PPAD-hardness, LP duality in zero-sum games, no-regret learning bounds, extensive-form imperfect information, and incentive compatibility results.
- 02
From theory to hardware or code
Ask what they implemented: CFR or CFR+ variants, Lemke-Howson, double oracle or PSRO, Gambit or OpenSpiel usage, auction simulators, and the scale of games actually solved.
- 03
Research judgement
Test how they choose problems: when abstraction or sampling is acceptable, when a solution concept is the wrong model, and how they detect that a proof or benchmark is misleading.
- 04
Explaining it to non-specialists
Assess explanation to product, policy, or trading stakeholders: translating incentive compatibility, revenue equivalence, or strategy exploitability into pricing, matching, or auction decisions without formal notation.
Pre-screening questions to ask Game Theorist candidates
12 questions grouped by what they test. Ask the same set in every screen and score answers on a consistent scale, or send them as an async video screen and compare answers side by side.
Models that informed decisions
3 questions01Can you explain Nash equilibrium and give a real situation where it applies?
Listen forA concrete application with the assumptions stated, and awareness that an equilibrium is not automatically a prediction.
A textbook definition with a textbook example, or equilibrium presented as what will happen.
02Explain Stackelberg competition and its relevance in industry.
Listen forThe commitment assumption examined, with a real market where first-mover advantage did or did not hold.
The model recited with no discussion of whether commitment is credible in practice.
03Discuss the role of game theory in network design and resource allocation.
Listen forApplied work on congestion or allocation with an outcome, including where selfish routing costs efficiency.
Applications described in the abstract, or no problem they have modelled with real data.
Solution concepts
3 questions04Describe subgame perfection and why it matters in strategy.
Listen forThe refinement explained through what it rules out, with an example of a non-credible threat in practice.
Definition given with no account of why the refinement is needed.
05What are mixed strategies, and how do they differ from pure strategies?
Listen forA clear account of when mixing is rational and how a mixed equilibrium should be interpreted in a real setting.
Mixed strategies described mechanically, or interpreted as players literally randomising in every context.
06What are correlated equilibria, and how do they generalise Nash equilibrium?
Listen forThe role of a signalling device explained, with an application where correlation improves on the Nash outcome.
The concept named with no explanation of what the correlating device does.
Information and design
4 questions07Can you discuss the role of information asymmetry in games and how it affects outcomes?
Listen forSignalling and screening distinguished, with a market example where asymmetry changed the equilibrium.
Asymmetry described generally, or no distinction between signalling and screening.
08What are Bayesian games, and how do they differ from games of complete information?
Listen forTypes and beliefs explained, with the common prior assumption acknowledged as a strong requirement.
The framework described with no mention of what the common prior assumption demands.
09Can you explain the importance of mechanism design in creating effective and fair systems?
Listen forIncentive compatibility and participation constraints treated as real design requirements, with an applied example.
Mechanism design described as designing rules, or impossibility results not acknowledged.
10What is the role of auction theory, and can you describe the main auction formats?
Listen forFormats compared on bidder behaviour and revenue, with awareness of where equivalence results break down.
Formats listed with no behavioural comparison, or revenue equivalence stated without its conditions.
Explaining the result
2 questions11How does the minimax algorithm work, and where is it typically used?
Listen forThe algorithm explained with its computational limits, including why pruning and heuristics are necessary.
The algorithm described with no awareness of the search cost or where it becomes infeasible.
12How do Markov decision processes connect with game theory, particularly in reinforcement learning?
Listen forThe step from single agent to multi-agent explained, with non-stationarity identified as the core difficulty.
Multi-agent settings treated as a straightforward extension, or convergence assumed as in single-agent learning.
How to score responses
Score every candidate on the same four criteria immediately after the screen. At this stage you are shortlisting for panel interviews, not making the final call.
Theoretical command
35%5States hardness results and convergence guarantees precisely, distinguishes coarse correlated from Nash equilibria, and cites specific theorems rather than gesturing at them.
From theory to hardware or code
30%5Names solvers they wrote or extended, quotes game tree sizes, exploitability numbers, and runtime, and shows the code or published artefact.
Research judgement
20%5Describes abandoned directions with reasons, questions whether equilibrium is the right target, and separates modelling error from algorithmic error.
Explaining it to non-specialists
15%5Explains a mechanism design trade-off in plain terms with a concrete example, and has written memos or briefings non-specialists acted on.
Applied game theory fails on assumptions rather than mathematics, and real players are not the model's players. A one-way video screen asks what it assumed.
Try it on HirevireScreening FAQ
Process basics
How long should a pre-screening round for this role take?
Fifteen minutes across eight to ten questions, answered async. Enough to hear one applied model, test their command of the core concepts, and check whether they state assumptions unprompted.
Do I need a specialist to review the answers?
For the technical questions, yes. You can still judge whether someone states limits, distinguishes a modelling choice from a fact, and explains clearly, which are strong signals on their own.
Evaluating answers
What is the strongest signal when screening a game theorist?
Naming the assumptions a result depends on without being asked. Strong candidates volunteer them because they know that is where applied work fails. Anyone presenting an equilibrium as a prediction is overreaching.
How do I judge applied experience?
Ask what decision the model informed and whether the predicted behaviour occurred. Theorists with applied experience can say what the model got wrong. Anyone whose models always matched behaviour has not tested one.
Go deeper on this role
Sanat has been hiring since 2012 and watching the recruitment industry change up close ever since, and turned that screening process into Hirevire's video screening platform. LinkedIn
