Today I want to share with you that we recently helped our students pass the Jane Street interview case, I wanted to write this article mainly because I think theJane StreetThe interviews are not entirely dependent on talent or background, but can be attacked with targeted and extensive training. While Jane Street's team is full of top talent (e.g., Target school honors students, Putnam top 100, IMO medalists, etc.), taking advantage of the opportunities available gives the average person the same chance to get on the platform.
The main character of the story is a junior MLB student who, after receiving an interview with Jane Street, immediately approached our Programhelp team to help him prepare for the interview. Here's the full story of how we helped him get through three rounds of interviews, step-by-step.
Round 1: Telephone technical interviews
Interviewer question, "Toss a coin continuously until it comes up heads twice in a row, find the expected number of tosses." The trainee initially tries to violently enumerate all paths, but is unable to build a valid equation quickly due to the complexity of the branching, which leads to confusing recursive logic. His thinking was clearly wrong, so we activated the "Markov chain" conditioning that we had developed through training and gave him a hint through the secondary device, and he quickly drew a state transfer diagram on the whiteboard:
E = 1 + 0.5 E₁ + 0.5 E E₁ = 1 + 0.5 0 + 0.5 E The three equations are solved to give E = 6, and the answer is limited to 90 seconds. The interviewer nods in satisfaction.
Round two:Coding
Required to write efficient code in Python in 30 minutes and must pass a test case given by the interviewer on the spot. Participants were presented with a problem: "Find a target value in an infinitely long array (known to exist and the array is incrementing and then decrementing)".
Immediately after solving this problem, we give the code in the secondary device and voice give the code explanation.
def find_in_infinite_array(arr, target).
# Initial boundaries
left, right = 0, 1
# Extend the right boundary until an interval containing the target value is found
while arr[right] < target.
left = right
right *= 2 # Exponentially extend the right boundary
# Perform a bisection search within a finite range
while left <= right.
mid = (left + right) // 2
# If mid is equal to target, return index
if arr[mid] == target.
return mid
# If mid is less than target, target is in incremental segment
elif arr[mid] < target.
left = mid + 1
# If the mid value is greater than the target value, the target value is in the decreasing segment
else: right = mid - 1
right = mid - 1
# if not found, return -1 (according to the description of the question, the target value must exist)
return -1Our timely delivery and the confident performance of the trainees fought a perfect match and the interviews were successful in the final round.
Third round of interviews: real-time modeling
The third round was Jane Street's signature Live Problem Solving, where the interviewer threw out an open-ended scenario: "Assuming you're on the trading floor and you receive a batch of orders for a stock in real time, with the price obeying a geometric Brownian motion, how do you devise a hedging strategy that would make the position risk-neutral within 10 minutes? How do you design a hedging strategy to make the position risk neutral within 10 minutes?"
We send the core framework tip "Risk Neutral = Delta Hedging + Frictionless Assumptions" (the vibration signal corresponds to the keywords we have trained in advance: "Black-Scholes Delta Calculation → Discrete Rebalancing → Tolerance Correction") through the sub-device. After receiving the cue, the trainee first proposes a dynamic delta hedging strategy based on the Black-Scholes model (dividing 10 minutes into N intervals, calculating Δ = Φ(d₁) in real time and adjusting the underlying asset position), and then, in response to the interviewer's question about transaction costs, adds the realistic correction of "Setting a threshold for delta deviation to reduce the frequency of rebalancing", and "Setting a threshold for delta deviation to reduce the frequency of rebalancing". In response to the interviewer's question about trading costs, the interviewer added "setting a threshold for delta deviation to reduce the frequency of rebalancing" as a realistic correction program. The whole set of answers is logical and clear, from theoretical models to practical details, and the interviewer recognized his structured thinking.
final result
Through our help, the student gradually overcame the difficulties during the three rounds of interviews and finally succeeded in getting an offer from Jane Street, which not only proves the importance of targeted training, but also reaffirms that ordinary people can also get into the top quantitative trading firms through hard work and scientific preparation. Whether you are a Target School student or an applicant from a non-traditional background, the core competency of quantitative interviews is never "talent" but "using the right method". ImmediatelyContact UsTo start your Jane Street pass program.
