Free Interview Resources
Free practice questions, preparation advice, and expert insights for Economics, Finance and Data Science interviews at Imperial College London.
Real Economics, Finance and Data Science interview questions in the style Imperial College London asks. Try answering each one aloud before you reveal the hint.
A coffee shop raises its price by 10% and weekly sales fall by 6%. Estimate the price elasticity of demand and explain what should happen to total revenue.
Problem-Solving
Hint
Start by writing elasticity as percentage change in quantity divided by percentage change in price, then link the magnitude to revenue.
A government gives every household a one-off energy rebate. Sketch verbally what might happen to demand, supply, prices and welfare in the short run.
Problem-Solving
Hint
Separate demand-side effects from supply constraints, then state which assumptions matter most.
Using the return distribution below, calculate the expected return and explain one limitation of using expected return alone.
Problem-Solving
Hint
Multiply each return by its probability, add the results, then discuss risk or dispersion.
A regression finds that areas with more police have more recorded crime. What are three possible explanations before concluding that police cause crime?
Problem-Solving
Hint
Think about reverse causality, omitted variables and measurement choices.
Two groups each show higher employment after training, but the combined dataset shows lower employment for trained people. How could that happen?
Problem-Solving
Hint
Look for a hidden grouping variable that changes the composition of the trained and untrained groups.
Structured interviews that combine technical problem-solving with motivation and personal statement discussion.
Imperial interviews vary by department. Engineering and Computing tend to be technical with problem-solving elements. Medicine uses a Multiple Mini Interview (MMI) format with several short stations. Most interviews last 15-30 minutes and may include a presentation or group exercise.
Interview Invitation
Late Nov
Arrival to Interview
Early Dec
Technical Question
Mid Dec
Decision
Early Jan
Interview Invitation
Late Nov
Arrival to Interview
Early Dec
Technical Question
Mid Dec
Decision
Early Jan
An online platform shows you only successful investment strategies from the past year. Explain the statistical problem and how you would design a better comparison.
midHint
Ask which observations are missing and what benchmark or control group would make the comparison fair.
Explain the difference between correlation and causation using an example from economics, finance or public policy.
entryHint
Give a concrete example, then say what evidence would move you closer to a causal claim.
Why might a central bank raise interest rates when inflation is high, and who might gain or lose from that policy?
midHint
Track the effect through borrowing, saving, spending and expectations, then discuss distributional consequences.
What makes a dataset representative, and why would that matter for a company using machine learning to approve loans?
midHint
Define the target population first, then compare it with the data-generating process.
What is opportunity cost, and how would you apply it to a student's decision to take a gap year before university?
entryHint
List the next-best alternative and include both financial and non-financial trade-offs.
Your personal statement mentions a data project. What was the most important assumption you made, and how would the conclusion change if that assumption failed?
midHint
Choose one assumption that genuinely affects the result rather than listing every small limitation.
Which part of the Imperial course structure most strongly explains your choice of this programme rather than a traditional economics degree?
entryHint
Link one specific course feature to a genuine academic interest or future direction.
Tell me about a recent economic or financial news story you followed. What data would you want before forming a confident view?
midHint
Move from description to evidence: identify variables, sources, comparisons and uncertainty.
If public transport were made free in London, would congestion definitely fall?
hardHint
Avoid a yes/no answer at first: identify substitute journeys, induced demand, funding and measurement.
Formula One teams use enormous datasets during races. What is one decision where better data could still lead to a worse outcome?
midHint
Think about uncertainty, incentives, overfitting and the cost of acting too late.
12+ weeks
8-12 weeks
4-6 weeks
1-2 weeks
the week of
Unlock the full guide
Free Resource
The Complete Imperial College London Economics, Finance and Data Science Interview Guide
Enter your email to unlock the full question bank, worked approaches, a week-by-week prep roadmap, and the mistakes that cost offers.
Practice with an Imperial Economics, Finance and Data Science graduate who's been through it.
Book Mock Interview →Watch & Learn
Quick review of elasticity and revenue logic for entry-level interview scenarios.
Useful for revisiting the language of scarcity, markets and equilibrium.
Supports clear explanations of inflation, interest rates and policy trade-offs.
Useful for intuitive machine-learning discussion without needing advanced maths.
Concise refresher for demand/supply curve shifts and verbal reasoning.
All videos are the property of their respective creators.
Further Reading
by CORE Econ Team
Free introductory economics text with real-world data and policy framing that fits the programme's applied emphasis.
by CORE Econ Team
Useful for practising how economists move from question to data, measurement and interpretation.
by Tim Harford
Accessible examples of incentives, markets and everyday economic reasoning.
by Charles Wheelan
Builds intuitive explanations of probability, regression and statistical misuse.
by Nate Silver
Good for discussing prediction, uncertainty and why models fail.
by UAT-UK
Official archive of historic TMUA papers; UAT-UK says the question style and content specification remain unchanged.
by UAT-UK
Best source for timings, format, scoring and test-day constraints.
by Bank of England
Strong source for interview-ready explanations of money, inflation, rates and financial stability.
by Our World in Data
Good practice for interpreting real charts, sources, definitions and uncertainty.
by Stephen J. Dubner and Freakonomics Radio Network
Named by an Imperial EFDS student as a useful source for economics-and-data topics.