E. Shaw's India quant and technical interviews blend rigorous probability, combinatorial logic, and clean derivations, reflecting a research-driven firm. In 2026 expect expected-value problems solved via recurrence relations (expected flips to see two consecutive heads), classic combinatorial puzzles (the 25-horses racing problem), and probability and estimation questions where the reasoning matters more than the memorised answer. For technical roles, algorithms and data-structures depth is also tested. Interviewers reward a minimal, rigorous argument and honest handling of what you are unsure about. Practise deriving expected values from first principles, structuring combinatorial arguments cleanly, and narrating your logic so a sceptical interviewer can follow every step.
About DE Shaw
DE Shaw India (DESI) is the Indian R&D and technology subsidiary of the global quantitative hedge fund DE Shaw, based in Hyderabad. It is the primary engineering and research engine for the entire DE Shaw group globally.
- Products
- Proprietary quantitative trading strategies · Portfolio management and risk systems · Scientific computing and HPC infrastructure · Anthill simulation platform · Internal fintech (DE Shaw payments, internal banking tools)
- Competitors
- Jane Street · Tower Research Capital · Two Sigma · Citadel · AQR Capital
- Scale
- ~3,000 employees in Hyderabad (DESI is DE Shaw's largest office globally). Privately held. DE Shaw AUM ~$60B+.
DE Shaw recruitment process
01
Apply or get sourced; online assessment or recruiter screen
02
Probability and quantitative-reasoning round
03
Technical and algorithms rounds (for technical roles)
04
Final rounds with the team, then offer
What to expect in each round
01
Round 1 (45-60 min)
probability and combinatorial-reasoning round.
02
Round 2 (45-60 min)
expected-value derivations and estimation questions.
03
Round 3 (45-60 min)
algorithms and data-structures round for technical roles, or deeper quant for research roles.
Technical questions DE Shaw asked
Sourced from 2+ candidate post-mortems. Hit Practice to answer any one with AI voice feedback.
- 01
Medium
Reverse a linked list in O(1) extra space. Then explain when you'd use this in production.
- 02
Easy
What is the difference between a class and an object? Give an example.
- 03
Easy
Write a SQL query to find the second-highest salary in a department.
- 04
Easy
What is normalisation in databases? When would you de-normalise?
- 05
Easy
What's the difference between a stack and a queue? Give a real-world use case for each.
- 06
Hard
Given a stream of integers, design a data structure that returns the median in O(log n).
- 07
Medium
You have a service that's slow only on Tuesdays. Walk me through how you'd debug.
- 08
Hard
Here's 200 lines of payment-processing code with several intentional bugs. Find them and explain the production impact of each.
- 09
Medium
Explain webhooks vs. polling for a developer who has never built a payment integration. You have 4 sentences.
- 10
Hard
Walk me through Razorpay's fraud-detection model. How would you reduce false positives without increasing chargeback losses?
- 11
Medium
We see UPI failure rates spike at 9pm on weekends. How would you debug and what's your hypothesis?
- 12
Easy
What's 54% of 110? You have 10 seconds.