Hudson River Trading (HRT) is a top-tier US electronic market-making firm. Quant Researcher, AT (Algorithm Engineer), and Core Dev tracks remain open in 2026. The OA platform is CodeSignal, harder than Optiver Trader's mental-math OA — main lines: Q1-Q4 classic algorithms + Pandas data + probability reasoning. Below: full pipeline + Akuna / IMC comparison + OA assistance.
HRT OA Snapshot
| Dimension | Detail |
|---|---|
| Platform | CodeSignal Industry Coding Framework (ICF) |
| Duration | 70 minutes |
| Questions | 4 (Q1 Easy → Q4 Hard) |
| Difficulty | LC Medium-Hard pace |
| Grading | Auto + hidden stress |
Q1-Q4 Problem Lines
Q1 (Easy): Array / String
def find_pivot(arr):
total = sum(arr)
left = 0
for i, x in enumerate(arr):
if left == total - left - x:
return i
left += x
return -1
Q2 (Medium): Hash / Binary Search
def smallest_missing_positive(arr):
nums = sorted(set(x for x in arr if x > 0))
expected = 1
for x in nums:
if x == expected:
expected += 1
elif x > expected:
return expected
return expected
Q3 (Medium-Hard): DP / Graph — LC 1235 / 1654 / 787
Q4 (Hard): Bitmask / Interval / Number Theory — LC 956 / 1601 / 1771
Line 2: Pandas Data Problem (AT Track)
import pandas as pd
def rolling_ic(df, window=60):
df = df.sort_values(['symbol', 'date']).copy()
df['ret_next'] = df.groupby('symbol')['ret'].shift(-1)
def ic(group):
return group['signal'].rolling(window).corr(group['ret_next'])
df['ic60'] = df.groupby('symbol', group_keys=False).apply(ic)
return df[['date', 'symbol', 'ic60']]
shift(-1) produces NaN on the last row — drop it.
Line 3: Probability Reasoning
"3 independent coins, P(H) = 0.6, 0.5, 0.4. P(at least 2 heads)?"
P(3) = 0.6 × 0.5 × 0.4 = 0.12 P(exactly 2) = 0.6×0.5×0.6 + 0.6×0.5×0.4 + 0.4×0.5×0.4 = 0.38 P(≥2) = 0.5
HRT vs Akuna vs IMC
| Dimension | HRT | Akuna | IMC |
|---|---|---|---|
| Platform | CodeSignal ICF | HackerRank + in-house | HackerRank |
| Questions | 4 in 70 min | 3 in 60 min | 3 in 60 min |
| Topics | Algo + Pandas + probability | Algo + Python OOP | Algo + mental math |
| Pass bar | 4 AC ≥ 50% | 3 AC ≥ 70% | 3 AC + mental math ≥ 50/80 |
| Culture | Math / systems | Python / OOP | High-speed cadence |
All three share a follow-up brain-teaser interview after the OA — prep separately.
5-Day Sprint
| Day | Task |
|---|---|
| D1 | LC Hard bitmask / number theory ×4 |
| D2 | Pandas rolling + groupby + corr ×5 |
| D3 | 25 probability brain teasers |
| D4 | Timed 70-min CodeSignal Q1-Q4 mock |
| D5 | Gap drills + Akuna / IMC backfill |
FAQ
Which language for HRT OA?
Mostly Python / C++. AT track leans C++ (perf problems); Core Dev / Researcher lean Python.
Must I solve Q4 Hard?
Not required. Community reports: 3 AC + Q4 partial → phone screen; 4/4 → onsite direct.
Result timeline?
Usually 7–14 days. Pass → brain teaser + tech screen; full loop 4–6 weeks.
Does HRT Quant Researcher require a PhD?
Not strictly, but ~80% of candidates have STEM PhDs or top-1% competition backgrounds. AT / Core Dev are more flexible.
Preparing HRT / Akuna / IMC OA?
We were glad to help this cohort pass HRT CodeSignal Q1-Q4 OA. Many candidates told us they couldn't even finish reading Q4 Hard's prompt in 70 minutes, let alone produce brute force. HRT's OA punishes perfectionism — clear Q1-Q3 first, then attack Q4 for partial credit.
If you're prepping HRT, Akuna, IMC, SIG, Optiver, or Citadel market-making / HFT Quant / AT / Core Dev OA / VO and feel pacing's unstable or Q4 Hard is unreachable, contact oavoservice. We tailor OA / VO assistance to your gaps and connect Q1-Q4 pacing + Pandas + probability into one practice loop.
👉 Add WeChat: Coding0201 — grab the HRT OA assistance pack.
Contact
Email: [email protected]
Telegram: @OAVOProxy